Elsevier

Oral Oncology

Volume 96, September 2019, Pages 153-160
Oral Oncology

Exploring the role of Mir204/211 in HNSCC by the combination of bioinformatic analysis of ceRNA and transcription factor regulation

https://doi.org/10.1016/j.oraloncology.2019.07.024Get rights and content

Highlights

  • A ceRNA network of 178 lncRNAs, 19 miRNAs and 55 mRNAs in HNSCC was built.

  • A TF regulatory network was constructed based on the PPI network of 52 hub genes.

  • 11 lncRNAs and 14 mRNAs were found to be survival-related in HNSCC.

  • miR-204/211 revealed to be the promising key miRNAs in HNSCC.

Abstract

Objectives

This study aimed to reveal the regulatory roles of microRNAs in head and neck squamous cell carcinoma (HNSCC) through comprehensive ceRNA, miRNA-transcription factor (TF)-hub gene network and survival analysis.

Materials and methods

Expression analysis was performed using the 'edgeR' package based on The Cancer Genome Atlas database. The ceRNA network was screened by intersecting prediction results from miRcode, miRTarBase, miRDB and TargetScan. GSE30784, GSE59102 and GSE107591 from the Gene Expression Omnibus repository were chosen for cross-validation. Hub genes were identified using a protein-protein interaction network constructed by Search Tool for the Retrieval of Interacting Genes. The Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TTRUST) was utilized to map the miRNA-TF-Hub gene network. Patient overall survival was analyzed using the ‘survival’ package in R. Structural and functional analysis of miR-204/211 was based on miRbase and RNAstructure.

Results

A ceRNA network of 178 lncRNAs, 19 miRNAs and 55 mRNAs was generated, and a TF regulatory network with 11 miRNAs, 11 TFs and 18 hub genes was constructed from the 52 hub genes identified through the protein–protein interaction (PPI) network. Survival analysis demonstrated that the dysregulated expression of 11 lncRNAs and 14 mRNAs was highly related to overall survival. Furthermore, miR-204 and miR-211 were significantly involved in the network with identical mature structures, indicating them as key miRNAs in HNSCC.

Conclusion

This study reveals the comprehensive molecular regulatory networks centralized by miRNAs in HNSCC and uncovers the crucial role of miR-204 and miR-211, which may become potential diagnostic and therapeutic targets.

Introduction

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer worldwide, with a high incidence of 500,000 newly diagnosed cases per year, a high rate of metastatic recurrence, and a five-year overall survival rate as low as approximately 50% [1], [2], [3], [4], [5]. Emerging targeted therapies, such as monoclonal antibodies against epidermal growth factor receptor (EGFR), tyrosine kinase inhibitors, the phosphoinositide 3-kinase (PI3K)/AKT/ mammalian target of rapamycin (mTOR) pathway pathway inhibitors, and immunotherapy agents such as anti-PD-1/PD-L1 antibodies and TLR-8 agonists, are under development, but with limited efficacy [6]. Therefore, an increased understanding of HNSCC pathogenesis at the molecular level is urgently needed to identify novel therapeutic strategies.

The gene expression network of cancer has been predicted to be intricate and fathomable, involving a large variety of players, such as transcription factors (TFs), microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and coding genes. Among all factors, miRNAs predominately play direct roles through translation inhibition and mRNA degradation [7], [8], while two or more miRNAs with similar sequences can frequently reside in clusters and function synergistically in the pathogenesis of various diseases [9], [10], [11]. Being responsible for oncogenesis, miRNAs possess great potential to be biomarkers in HNSCC and other cancers [8], [9], [12].

Several crosstalk mechanisms have gained ground. For example, miRNAs act as a bridge between lncRNAs and targeted mRNAs. Salmena et al. proposed the competing endogenous RNA (ceRNA) hypothesis: the same miRNA response elements (MRE) are shared among lncRNAs and mRNAs, enabling lncRNAs to interact with miRNAs as “sponges” and suppress their impact on mRNAs [13]. CeRNA networks have been verified in multiple cancers, including HNSCC [14], [15], [16], [17], [18]. Another factor at play is the impact of miRNAs on TFs. Compared with coding genes, a miRNA is twice as likely to choose a TF as its target [19], which entails indirect regulation on the transcriptional process besides its post-transcriptional role. Furthermore, a mathematical model quantified the maximal post-transcriptional regulatory power achievable by miRNA-mediated crosstalk in the case of ceRNA circuits. This model clarified that miRNA-mediated control could eclipse other regulation, such as direct transcriptional control via DNA-binding factors [20]. In conclusion, the current scenario indicates that besides its widely recognized noise-buffering role, miRNAs may indeed act as master regulators of gene expression.

Considering the intricate regulatory roles of miRNAs in affecting cell phenotype, a comprehensive and systematic analysis of their roles in lncRNA-miRNA-mRNA, miRNA-TF-mRNA triplet regulatory networks and related survival effects remains obscure. An integrated regulatory network centralized by miRNAs would contribute greatly to the understanding of the oncogenesis of HNSCC. Therefore, in our study, we explored The Cancer Genome Atlas database (TCGA) database and 3 related Gene Expression Omnibus (GEO) datasets to illustrate the pathogenesis of HNSCC. With multiple bioinformatic strategies, we established both a ceRNA network connecting lncRNAs, miRNAs, and mRNAs and a TF regulatory network connecting miRNAs, TFs and hub genes. We also conducted a closely related survival analysis illustrating the pathogenesis of HNSCC. As a result, we identified miR-204 and miR-211 as a promising cluster in the HNSCC pathological process, shedding light on new diagnostic and therapeutic approaches.

Section snippets

Microarray data acquisition

Expression data on HNSCC from the TCGA database (https://cancergenome.nih.gov/) were downloaded on June 8, 2018. The RNA-seq data include 502 HNSCC samples and 44 normal samples, while the miRNA-seq data include 525 HNSCC samples and 44 normal samples. Our study adhered to the TCGA publication guidelines and data access policies (http://cancergenome.nih.gov/publications/publicationguidelines).

Differentially expressed gene analysis

Based on the data from TCGA, the Empirical Analysis of Digital Gene Expression Data in R (edgeR)

Identification of differentially expressed mRNAs, miRNAs and lncRNAs

The workflow of our study is shown in Fig. 1. We collected HNSCC-related expression data from TCGA, including RNA-seq data with 502 HNSCC samples and 44 normal samples as well as miRNA-seq data with 525 HNSCC samples and 44 normal samples. Volcano plots were used to assess differentially expressed genes. In total, 3070 DE mRNAs were screened out, including 1650 downregulated and 1420 upregulated mRNAs in cancerous samples. Of the 2612 DE lncRNAs, 771 were downregulated, and 1841 were

Discussion

Multiple studies have revealed the complex gene expression pattern during oncogenesis. In some circumstances, miRNA-mediated control may indeed act as a master regulator of gene expression [20]. Clarification of such interactive regulatory networks in cancers could provide new therapeutic opportunities. However, a comprehensive analysis based on the centric role of miRNAs in HNSCC remains unavailable. Therefore, we aimed to explore the effects of miRNAs in HNSCC pathogenesis focusing on both

Conclusion

In summary, we established lncRNA-miRNA-mRNA and miRNA-TF-mRNA regulatory networks and then introduced survival analysis to reveal the possible role of miRNAs in HNSCC. On the one hand, the promising centric standing of miR-204/211 that we found may shed light on improved diagnosis or targeted treatment of HNSCC; on the other hand, a comprehensive approach to pathogenesis analysis of other diseases is provided.

Declaration of Competing Interest

Jingyi Cai, Yeke Yu, Yuzi Xu, Hao Liu, Jiawei Shou, Liangkun You, Hanliang Jiang, XuFeng Han, Binbin Xie, Weidong Han declare that: we have no proprietary, financial, professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled: Exploring the role of Mir204/211 in HNSCC by the combination of bioinformatic analysis of ceRNA and transcription factor

Acknowledgements

This work was supported by the Zhejiang Natural Sciences Foundation Grant (LQ18H160008, Q17H160042, LY17H160029, LY18H160007), the Ten Thousand Plan Youth Talent Support Program of Zhejiang Province, and the Zhejiang medical innovative discipline construction project-2016.

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