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Microrna and Gene Networks in Human Laryngeal Cancer

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Microrna and Gene Networks in Human Laryngeal Cancer EXPERIMENTAL AND THERAPEUTIC MEDICINE 10: 2245-2252, 2015 microRNA and gene networks in human laryngeal cancer FENGYU ZHANG1,2, ZHIWEN XU1,2*, KUNHAO WANG1,2, LINLIN SUN1,2, GENGHE LIU1,2 and BAIXU HAN1,2 1College of Computer Science and Technology; 2Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, Changchun, Jilin 130012, P.R. China Received May 30, 2014; Accepted March 25, 2015 DOI: 10.3892/etm.2015.2825 Abstract. Genes and microRNAs (miRNAs) are considered is involved in the regulation of cellular differentiation and to be key biological factors in human carcinogenesis. To development and metabolic processes (2). date, considerable data have been obtained regarding genes Transcription factors (TFs) and microRNAs (miRNAs) and miRNAs in cancer; however, the regulatory mechanisms have crucial roles in the regulation of gene expression (3). TFs associated with the genes and miRNAs in cancer have yet to are proteins that bind to cis-regulatory elements located in be fully elucidated. The aim of the present study was to use the upstream regions of genes in order to activate or suppress the key genes and miRNAs associated with laryngeal cancer transcription, thereby acting to regulate gene expression at the (LC) to construct three regulatory networks (differentially transcriptional level. TFs may function alone or in combination expressed, LC-related and global). A network topology of with other proteins (4). miRNAs are evolutionarily conserved, the development of LC, involving 10 differentially expressed endogenous, non-coding RNAs that post-transcriptionally miRNAs and 55 differentially expressed genes, was obtained. modulate gene expression and are associated with tumori- These genes exhibited multiple identities, including target genesis (5). Differentially expressed genes and miRNAs are genes of miRNA, transcription factors (TFs) and host genes. significant factors in the development, metastasis and therapy The key regulatory interactions were determined by comparing of LC. miR-21, for example, has been suggested to play an the similarities and differences among the three networks. The oncogenic role in the cellular processes of LC (6), and c-Myc nodes and pathways in LC, as well as the association between is highly expressed at the protein level in LC (7). each pair of factors within the networks, such as TFs and miRNAs target thousands of human genes, known as target miRNA, miRNA and target genes and miRNA and its host genes; knowledge of these target genes is important for the gene, were discussed. The mechanisms of LC involved certain analysis of the biological functions of miRNAs (8). A number key pathways featuring self-adaptation regulation and nodes of databases, including those that are computationally (9) and without direct predecessors or successors. The findings of the experimentally (10,11) validated, provide an adequate resource present study have further elucidated the pathogenesis of LC to facilitate an understanding of the associations between and are likely to be beneficial for future research into LC. miRNAs and their targets. Certain miRNAs are located within genes known as host genes, and these miRNAs are transcribed Introduction in parallel with their host transcripts. Two different transcrip- tion classes of miRNAs have been identified: Exonic and Laryngeal cancer (LC) is one of the most common types of intronic (12). Baskerville and Bartel (13) indicated that a close head and neck cancer. A large number of protein-coding and association exists between intronic miRNA and its host gene. non-coding genes are known to be differentially expressed Intronic miRNA and its host gene are usually expressed in a in LC cells, indicating a functional switch (1). This gene coordinated manner in biological progression, and typically expression is regulated at the post-transcriptional level, and work in combination to effect a biological function and the alteration of signaling pathways (14). The host gene is consid- ered in the network of differentially expressed factors when its corresponding miRNA is differentially expressed. The findings of the above studies suggest that miRNAs can either work together with or separately from their host genes in the Correspondence to: Miss. Fengyu Zhang, College of Computer progression of cancer. Science and Technology, Jilin University, 2699 Qianjin Street, The aim of the present study was to focus on the associations Changchun, Jilin 130012, P.R. China among the elements in LC by collecting information on the E-mail: [email protected] differentially expressed and cancer-related genes and miRNAs *Deceased involved in LC from databases and literature searches. Three types of association were considered: miRNAs targeting their Key words: transcription factors, microRNA, target genes, network, targets, TFs regulating their miRNAs and miRNAs locating laryngeal cancer within their host genes. Three networks (differentially expressed, LC-related and global) were built with the obtained data. Following network construction, comparisons were 2246 ZHANG et al: miRNA AND GENES IN LARYNGEAL CANCER made to find the similarities and differences among the three sequences [1,000 nucleotide (nt)] of the targets of differentially networks, and the regulatory pathways involving the differen- expressed genes were downloaded from the UCSC genome tially expressed elements and common TFs were separately browser database (20). The P-Match algorithm was used to extracted. We hypothesized that the pathways involving the identify the TFBSs in the 1,000-nt promoter region sequences, differentially expressed elements would have the most signifi- and these TFBSs were mapped onto the promoter region of the cant influence on the progression of LC, with the abnormal targets. The matrix library utilized by P-Match contains sets of modulation of these pathways promoting LC development. known TFBSs collected from the TRANSFAC database, and thus enables a wide range of TFBSs to be searched for. The Materials and methods vertebrate matrix and restricted high-quality criterion were used. The differentially expressed genes that were obtained Dataset of experimentally validated target associations were included in the LC-related gene set. The collected results between miRNAs and target genes. The experimentally vali- are referred to as dataset U5. dated dataset of the gene targets of each specific miRNA was extracted based on the data provided by Tarbase 5.0 (10) and Network construction at three levels. Three regulatory miRTarBase (11). The official symbols used in this study to networks were constructed to discuss the regulatory interac- unify all miRNAs and genes were obtained from the National tions between the genes and miRNAs in LC. The regulatory Center for Biotechnology Information (NCBI) database associations for the TFs, miRNAs, targets and host genes from (http://www.ncbi.nlm.nih.gov/gene/). The inclusion of these datasets U1, U2 and U3 were extracted. Following the combina- experimental data provides strong evidence to support the tion of the associations in these datasets, the global network study. The collected results are referred to as dataset U1. was derived. Differentially expressed and LC-related elements were separately extracted from U4 and U5, and then separately Dataset of experimentally validated regulatory associations mapped onto the global network. The differentially expressed between TFs and corresponding miRNAs. The dataset of the and LC-related networks were separately derived following interaction between the TFs and miRNAs was collected from the combination of the associations. TransmiR (15), which is a manually extracted database. The results from this process are referred to as dataset U2. Results Dataset of miRNAs and host genes. The host genes of Differentially expressed network in LC. Fig. 1 shows numerous respective miRNAs were manually established based on the important regulatory interactions among the differentially data obtained from miRBase (16) and the NCBI. Official expressed elements in LC. Each node displayed in the figure symbols and IDs were used to represent each host gene and represents a differentially expressed gene or miRNA. This miRNA. The collected results are referred to as dataset U3. network is composed of five TFs (TP53, PTEN, MYC, EGFR and NFKB1), the targets of miRNAs, miRNAs and their Differentially expressed miRNAs in LC and LC‑related host genes. With the exception of the host genes, all the other miRNAs. The differentially expressed miRNAs (overex- elements are differentially expressed in LC. There are three pressed, downregulated, and upregulated) in LC were mainly types of associations between the elements in LC: miRNAs extracted from mir2Disease (17), which is a manually created targeting genes, host genes containing miRNAs and genes database of differentially expressed miRNAs in various regulating miRNAs. Several types of the regulatory interac- human diseases. In addition, relevant literature was mined tions between miRNAs and genes are shown in Fig. 1. Most using PubMed (http://www.ncbi.nlm.nih.gov/pubmed) to notable are the five TF-related pathways. hsa-miR-106b identify differentially expressed miRNAs associated with LC, and hsa-miR-21 target PTEN, which regulates hsa-miR-21. the miRNAs involved in LC progression, and differentially hsa-miR-21 targets EGFR in LC. It is suggested that PTEN expressed and non-differentially expressed miRNAs. The could indirectly influence EGFR through
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