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

  • Authors:
    • Xiaobin Wang
    • Zeli Yin
    • Yanyun Zhao
    • Miao He
    • Chengyong Dong
    • Ming Zhong
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  • Published online on: January 27, 2020     https://doi.org/10.3892/mmr.2020.10964
  • Pages: 1647-1657
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Abstract

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.
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February 2020
Volume 21 Issue 3

Print ISSN: 1791-2997
Online ISSN:1791-3004

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APA
Wang, X., Yin, Z., Zhao, Y., He, M., Dong, C., & Zhong, M. (2020). Identifying potential prognostic biomarkers in head and neck cancer based on the analysis of microRNA expression profiles in TCGA database. Molecular Medicine Reports, 21, 1647-1657. https://doi.org/10.3892/mmr.2020.10964
MLA
Wang, X., Yin, Z., Zhao, Y., He, M., Dong, C., Zhong, M."Identifying potential prognostic biomarkers in head and neck cancer based on the analysis of microRNA expression profiles in TCGA database". Molecular Medicine Reports 21.3 (2020): 1647-1657.
Chicago
Wang, X., Yin, Z., Zhao, Y., He, M., Dong, C., Zhong, M."Identifying potential prognostic biomarkers in head and neck cancer based on the analysis of microRNA expression profiles in TCGA database". Molecular Medicine Reports 21, no. 3 (2020): 1647-1657. https://doi.org/10.3892/mmr.2020.10964