Literature DB >> 32016476

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

Xiaobin Wang1, Zeli Yin2, Yanyun Zhao3, Miao He3, Chengyong Dong2, Ming Zhong4.   

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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Year:  2020        PMID: 32016476     DOI: 10.3892/mmr.2020.10964

Source DB:  PubMed          Journal:  Mol Med Rep        ISSN: 1791-2997            Impact factor:   2.952


  5 in total

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Journal:  Mol Cell Biochem       Date:  2022-02-10       Impact factor: 3.396

2.  The Prediction of a 3-Protein-Based Model on the Prognosis of Head and Neck Squamous Cell Carcinoma.

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3.  Elevated expression of MKRN3 in squamous cell carcinoma of the head and neck and its clinical significance.

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Review 4.  Promising Biomarkers in Head and Neck Cancer: The Most Clinically Important miRNAs.

Authors:  Arsinoe C Thomaidou; Panagiota Batsaki; Maria Adamaki; Maria Goulielmaki; Constantin N Baxevanis; Vassilis Zoumpourlis; Sotirios P Fortis
Journal:  Int J Mol Sci       Date:  2022-07-26       Impact factor: 6.208

5.  PENK inhibits osteosarcoma cell migration by activating the PI3K/Akt signaling pathway.

Authors:  Hai-Ping Zhang; Zi-Liang Yu; Bing-Bing Wu; Fa-Rui Sun
Journal:  J Orthop Surg Res       Date:  2020-04-25       Impact factor: 2.359

  5 in total

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