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整合生物信息学分析以筛选甲状腺癌淋巴结转移中的枢纽基因。

Integrated bioinformatics analysis to screen hub genes in the lymph node metastasis of thyroid cancer.

作者信息

Lu Si, Zhao Rongjie, Shen Jie, Zhang Yu, Shi Jingjing, Xu Chenke, Chen Jiali, Lin Renbin, Han Weidong, Luo Dingcun

机构信息

Zhejiang Chinese Medical University Affiliated Hangzhou First Hospital, The Fourth Clinical College, Hangzhou First People's Hospital, Hangzhou, Zhejiang 310006, P.R. China.

Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310000, P.R. China.

出版信息

Oncol Lett. 2020 Feb;19(2):1375-1383. doi: 10.3892/ol.2019.11188. Epub 2019 Dec 6.

Abstract

Thyroid cancer (TC) is one of the most common types of malignancy of the endocrine-system. At present, there is a lack of effective methods to predict neck lymph node metastasis (LNM) in TC. The present study compared the expression profiles from The Cancer Genome Atlas between N1M0 and N0M0 subgroups in each T1-4 stages TC in order to identify the four groups of TC LNM-associated differentially expressed genes (DEGs). Subsequently, DEGs were combined to obtain a total of 493 integrated DEGs by using the method of Robust Rank Aggregation. Furthermore, the underlying mechanisms of LNM were investigated. The results from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses demonstrated that the identified DEGs may promote LNM via numerous pathways, including extracellular matrix-receptor interaction, PI3K-AKT signaling pathway and focal adhesion. Following construction of a protein-protein interaction network, the significance score for each gene was calculated and seven hub genes were screened, including interleukin 6, actinin α2, collagen type I α 1 chain, actin α1, calbindin 2, thrombospondin 1 and parathyroid hormone. These genes were predicted to serve crucial roles in TC with LNM. The results from the present study could therefore improve the understanding of LNM in TC. In addition, the seven DEGs identified may be considered as potential novel targets for the development of biomarkers that could be used in the diagnosis and therapy of TC.

摘要

甲状腺癌(TC)是内分泌系统最常见的恶性肿瘤类型之一。目前,缺乏有效的方法来预测TC中的颈部淋巴结转移(LNM)。本研究比较了癌症基因组图谱中各T1 - 4期TC的N1M0和N0M0亚组的表达谱,以鉴定四组与TC LNM相关的差异表达基因(DEG)。随后,通过稳健秩聚合方法将DEG合并,共获得493个整合的DEG。此外,还研究了LNM的潜在机制。基因本体论和京都基因与基因组百科全书通路富集分析的结果表明,鉴定出的DEG可能通过多种途径促进LNM,包括细胞外基质 - 受体相互作用、PI3K - AKT信号通路和粘着斑。构建蛋白质 - 蛋白质相互作用网络后,计算每个基因的显著性得分,并筛选出七个枢纽基因,包括白细胞介素6、辅肌动蛋白α2、I型胶原α1链、肌动蛋白α1、钙结合蛋白2、血小板反应蛋白1和甲状旁腺激素。预计这些基因在伴有LNM的TC中起关键作用。因此,本研究结果可提高对TC中LNM的认识。此外,鉴定出的七个DEG可被视为开发可用于TC诊断和治疗的生物标志物的潜在新靶点。

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