通过加权基因共表达网络分析(WGCNA)鉴定甲状腺乳头状癌中与LINC02454相关的关键通路和基因

IF 1.9 Q3 ENDOCRINOLOGY & METABOLISM Thyroid Research Pub Date : 2024-09-02 DOI:10.1186/s13044-024-00205-8
Yingjian Song, Lin Wang, Yi Ren, Xilei Zhou, Juan Tan
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引用次数: 0

摘要

背景:我们之前的研究表明,长基因间非编码RNA 02454(LINC02454)可能作为一种癌基因促进甲状腺乳头状癌(PTC)细胞的增殖并抑制其凋亡。本研究旨在探讨LINC02454与PTC肿瘤发生的相关机制:甲状腺癌 RNA 序列数据来自癌症基因组图谱(TCGA)数据库。应用加权基因共表达网络分析(WGCNA)确定与 PTC 密切相关的模块。利用京都基因组百科全书(KEGG)通路富集分析确定关键通路,并利用最大克隆中心性(MCC)拓扑方法确定枢纽基因。基因表达谱交互分析(GEPIA)数据库用于比较PTC样本和正常样本中关键基因的表达水平,并探索关键基因的预后价值。结果发现,前 5000 个可变基因的表达水平均高于正常样本:对前 5000 个可变基因进行了调查,然后对 8 个模块进行了分析,其中绿松石模块与 PTC 临床分期的正相关性最高。KEGG通路分析发现,ECM-受体相互作用通路和MAPK信号通路位居前两位。此外,通过 MCC 算法和 KEGG 分析还发现了五个关键基因(FN1、LAMB3、ITGA3、SDC4 和 IL1RAP)。在TCGA和GEO数据集中,这五个关键基因在甲状腺癌中的表达水平均显著上调,其中FN1和ITGA3与无病预后不良有关:我们的研究发现了与LINC02454相关的5个关键基因和2个关键通路,这可能揭示了LINC02454在PTC中发挥作用的潜在机制。
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Identification of LINC02454-related key pathways and genes in papillary thyroid cancer by weighted gene coexpression network analysis (WGCNA).

Background: Our previous study demonstrated that long intergenic noncoding RNA 02454 (LINC02454) may act as an oncogene to promote the proliferation and inhibit the apoptosis of papillary thyroid cancer (PTC) cells. This study was designed to investigate the mechanisms whereby LINC02454 is related to PTC tumorigenesis.

Methods: Thyroid cancer RNA sequence data were obtained from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify modules closely associated with PTC. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways, and the maximal clique centrality (MCC) topological method was used to identify the hub genes. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to compare expression levels of key genes between PTC samples and normal samples and explore the prognostic value of key genes. The key genes were further validated with GEO dataset.

Results: The top 5000 variable genes were investigated, followed by an analysis of 8 modules, and the turquoise module was the most positively correlated with the clinical stage of PTC. KEGG pathway analysis found the top two pathways of the ECM - receptor interaction and MAPK signaling pathway. In addition, five key genes (FN1, LAMB3, ITGA3, SDC4, and IL1RAP) were identified through the MCC algorithm and KEGG analysis. The expression levels of the five key genes were significantly upregulated in thyroid cancer in both TCGA and GEO datasets, and of these five genes, FN1 and ITGA3 were associated with poor disease-free prognosis.

Conclusions: Our study identified five key genes and two key pathways associated with LINC02454, which might shed light on the underlying mechanism of LINC02454 action in PTC.

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来源期刊
Thyroid Research
Thyroid Research Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
3.10
自引率
4.50%
发文量
21
审稿时长
8 weeks
期刊最新文献
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