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Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis

机译:基于生物信息学分析的肾上腺皮质癌关键生物标志物的筛选与鉴定

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摘要

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. The presently available understanding of the pathogenesis of ACC is incomplete and the treatment options for patients with ACC are limited. Gene marker identification is required for accurate and timely diagnosis of the disease. In order to identify novel candidate genes associated with the occurrence and progression of ACC, the microarray datasets, and , were obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed. A protein-protein interaction network (PPI) was constructed to identify significantly altered modules, and module analysis was performed using Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 228 DEGs were screened, consisting of 29 up and 199 downregulated genes. The enriched functions and pathways of the DEGs primarily included ‘cell division’, ‘regulation of transcription involved in G1/S transition of mitotic cell cycle’, ‘G1/S transition of mitotic cell cycle’, ‘p53 signaling pathway’ and ‘oocyte meiosis’. A total of 14 hub genes were identified, and biological process analysis revealed that these genes were significantly enriched in cell division and mitotic cell cycle. Furthermore, survival analysis revealed that AURKA, TYMS, GINS1, RACGAP1, RRM2, EZH2, ZWINT, CDK1, CCNB1, NCAPG and TPX2 may be involved in the tumorigenesis, progression or prognosis of ACC. In conclusion, the 14 hub genes identified in the present study may aid researchers in elucidating the molecular mechanisms associated with the tumorigenesis and progression of ACC, and may be powerful and promising candidate biomarkers for the diagnosis and treatment of ACC.
机译:肾上腺皮质癌(ACC)是一种罕见的恶性肿瘤,预后较差。目前对ACC的发病机理尚不完全了解,ACC患者的治疗选择有限。为了准确,及时地诊断疾病,需要基因标记鉴定。为了鉴定与ACC发生和发展相关的新候选基因,从基因表达综合公司获得了微阵列数据集和。鉴定差异表达基因(DEG),并进行功能富集分析。构建了蛋白质-蛋白质相互作用网络(PPI)以识别显着改变的模块,并使用搜索工具检索相互作用基因和Cytoscape进行模块分析。总共筛选了228个DEG,包括29个上调和199个下调的基因。 DEG的丰富功能和途径主要包括“细胞分裂”,“参与有丝分裂细胞周期的G1 / S过渡的转录调控”,“有丝分裂细胞周期的G1 / S过渡”,“ p53信号通路”和“卵母细胞”减数分裂”。总共鉴定出14个中枢基因,生物学过程分析表明这些基因在细胞分裂和有丝分裂细胞周期中显着富集。此外,生存分析显示AURKA,TYMS,GINS1,RACGAP1,RRM2,EZH2,ZWINT,CDK1,CCNB1,NCAPG和TPX2可能参与了ACC的发生,发展或预后。综上所述,本研究中鉴定出的14个中枢基因可能有助于研究人员阐明与ACC发生,发展有关的分子机制,并且可能是诊断和治疗ACC的有力且有希望的候选生物标记。

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