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Identifying potential prognostic biomarkers in head and neck cancer based on the analysis of microRNA expression profiles in TCGA database

机译:基于TCGA数据库中微小RNA表达谱的分析识别头部和颈部癌的潜在预后生物标志物

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摘要

The present study aimed to identify sensitive, specific and independent prognostic biomarkers in head and neck cancer (HNC) based on microRNA expression profiles and other high-throughput sequencing data in The Cancer Genome Atlas (TCGA) database. Identification of such prognostic biomarkers could provide insight into HNC diagnosis and treatment. The differential expression profiles of microRNAs between HNC tissues and adjacent cancer tissues in the TCGA database were analyzed (log fold-change >2; P<0.01). Univariate and multivariate Cox regression analyses of the differentially expressed microRNAs were performed to determine those significantly related to the survival of patients with HNC. The identified microRNAs were verified by survival and receiver operating characteristic curve analyses. To better predict prognosis, a combined prognostic model (risk equation) was established based on the risk coefficient of each microRNA, calculated by a multivariate Cox regression analysis, and the risk score was calculated. To explore the signaling pathways related to prognosis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed on the differentially expressed genes between the high-risk and low-risk groups, grouped according to the median risk score. A total of 89 differentially expressed microRNAs between HNC and adjacent cancer tissues were screened, 11 of which were identified as risk factors related to HNC survival by the univariate Cox regression analysis (P<0.05). The multivariate Cox regression analysis showed that three of the 11 microRNAs, hsa-miR-99a, hsa-miR-499a and hsa-miR-1911 (all P<0.01), were identified as independent risk factors significantly related to patient survival. The risk equation used was as follows: Risk score=(-0.1597 x hsa-miR-99a) + (0.1871 x hsa-miR-499a) + (0.1033 x hsa-miR-1911). KEGG and GO analyses showed that the JAK-STAT signaling pathway and some metabolic pathways were associated with HNC prognosis. The present study suggested that hsa-miR-99a, hsa-miR-499a and hsa-miR-1911 may serve as potential prognostic biomarkers in HNC.
机译:旨在本研究以确定灵敏,特异,在头部和颈部癌症基于在癌症基因组图谱(TCGA)数据库微小RNA表达谱和其他高通量测序数据(HNC)独立的预后生物标记。这样的预后生物标记物的鉴定可以提供洞察HNC的诊断和治疗。在TCGA数据库HNC组织和癌旁组织间微RNA的差异表达谱进行了分析(对数倍数变化> 2; P <0.01)。单因素和差异表达的microRNA的多元回归分析来确定这些显著关系到患者与HNC的生存。鉴定的微小RNA的生存和ROC曲线分析验证。为了更好地预测预后,组合预后模型(方程风险)成立基于每个微RNA的风险系数,通过多变量Cox回归分析计算,和风险分数计算。探索与预后有关的信号通路,京都基因与基因组百科(KEGG)和基因本体论(GO)分析是根据中值风险分数上的高风险和低风险群体之间的差异表达的基因进行的,分组。共HNC和癌旁组织之间差异89分表达的微小RNA进行了筛选,其中11被确定为通过单变量Cox回归分析(P <0.05)与HNC生存的风险因素。的多变量Cox回归分析显示,三个11个微小RNA,HSA-MIR-99A,HSA-的miR-499A和hsa-MIR-1911(所有P <0.01)的,被确定为显著与患者存活的独立危险因素。所用的风险方程为如下:风险分数=( - 0.1597 X HSA-MIR-99A)+(0.1871 X HSA-的miR-499A)+(0.1033 X HSA-MIR-1911)。 KEGG和GO分析显示,JAK-STAT信号通路和一些代谢途径,用HNC预后有关。目前的研究表明,HSA-MIR-99A,HSA-MIR-499A和HSA-MIR-1911可以作为HNC潜在的预后标志物。

著录项

  • 来源
    《Molecular medicine reports》 |2020年第2期|共11页
  • 作者单位

    China Med Univ Sch Stomatol Dept Orthodont Shenyang 110002 Liaoning Peoples R China;

    Dalian Med Univ Affiliated Hosp 2 Dept Gen Surg Div Hepatobiliary &

    Pancreat Surg 467 Zhongshan;

    China Med Univ Sch Pharm Dept Pharmacol Shenyang 110122 Liaoning Peoples R China;

    China Med Univ Sch Pharm Dept Pharmacol Shenyang 110122 Liaoning Peoples R China;

    Dalian Med Univ Affiliated Hosp 2 Dept Gen Surg Div Hepatobiliary &

    Pancreat Surg 467 Zhongshan;

    China Med Univ Sch Stomatol Dept Oral Histopathol 117 North Nanjing Ave Shenyang 110002;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 基础医学;
  • 关键词

    HNC; TCGA database; microRNA; prognostic analysis;

    机译:HNC;TCGA数据库;microRNA;预后分析;

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