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Comprehensive Analysis of Aberrantly Expressed Long Non‑Coding Rnas, Micrornas, and Mrnas Associated with the Competitive Endogenous RNA Network in Cervical Cancer

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Comprehensive Analysis of Aberrantly Expressed Long Non‑Coding Rnas, Micrornas, and Mrnas Associated with the Competitive Endogenous RNA Network in Cervical Cancer MOLECULAR MEDICINE REPORTS 22: 405-415, 2020 Comprehensive analysis of aberrantly expressed long non‑coding RNAs, microRNAs, and mRNAs associated with the competitive endogenous RNA network in cervical cancer PENG CHEN1, WEIYUAN ZHANG1, YU CHEN1, XIAOLI ZHENG1 and DONG YANG2 1Department of Obstetrics and Gynecology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University; 2Department of Obstetrics and Gynecology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100000, P.R. China Received June 02, 2019; Accepted March 20, 2020 DOI: 10.3892/mmr.2020.11120 Abstract. Cervical cancer is a common malignant disease lncRNA EPB41L4A‑AS1 may function as a pivotal regulator that poses a serious health threat to women worldwide. in carcinoma of the uterine cervix. Taken together, the present Growing research efforts have focused on protein-coding study has provided novel insights into investigating the poten- and non-coding RNAs involved in the tumorigenesis and tial mechanisms underlying tumorigenesis, development, and prognosis of various types of cancer. The potential molecular prognosis of cervical cancer, and presented new potential mechanisms and the interaction among long non-coding avenues for cancer therapeutics. RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs require further investigation in cervical cancer. In the present Introduction study, lncRNA, miRNA, and mRNA expression profiles of 304 primary tumor tissues from patients with cervical cancer and 3 Carcinoma of the uterine cervix is a severe malignant neoplasm solid normal tissues from The Cancer Genome Atlas (TCGA) that affects women globally (1). The mortality rate resulting dataset were studied via RNA sequencing (RNA‑seq). from cervical cancer remains high, and is second only to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and mortality rate of breast cancer (2). Cervical cancer is a complex Genomes (KEGG) pathway analyses were performed using R disease, and in addition to infection with the well-studied package clusterProfiler to annotate the principal functions of human papillomavirus (HPV), many other factors contribute differentially expressed (DE) mRNAs. Kaplan-Meier analysis to the tumorigenesis and progression of neoplasms. Aberrant was also conducted to investigate the effects of DElncRNAs, genes, multiparity, and smoking may exert a significant role DEmiRNAs, and DEmRNAs on overall survival. A total of in the risk of cervical cancer (3). Therefore, novel therapeutic 2,255 mRNAs, 133 miRNAs, and 150 lncRNAs that were and prognostic targets for cervical cancer are urgently needed. differentially expressed were identified with a threshold There is increasing evidence that long non-coding of P<0.05 and |fold change (FC)|>2. Functional enrich- RNAs (lncRNAs) and mRNAs fulfill key roles in tumorigenesis ment analysis indicated that DEmRNAs were enriched and tumor prognosis. Both lncRNAs and mRNAs may act as in cancer-associated KEGG pathways. Furthermore, 255 microRNA (miRNA) sponges that bind to miRNA response mRNAs, 15 miRNAs, and 12 lncRNAs that were significantly elements (MREs) to regulate gene expression (4). However, associated with overall survival in cervical carcinoma were the function of lncRNAs has yet to be adequately elucidated. also identified. Importantly, an miRNA‑mediated competi- Increasing evidence has suggested that lncRNAs participate tive endogenous RNA (ceRNA) network was successfully in various biological processes, including cell differentiation, constructed based on the expression profiles of DElncRNAs invasion, migration, and the cell cycle (5). The carcinogenic and DEmRNAs. More importantly, it was found that the mechanisms of lncRNAs at the molecular level, as well as their prognostic potential, are still largely unknown in cervical cancer. MiRNAs belong to the category of short non-coding RNAs, which may be either upregulated or downregulated in malignant tumors and may regulate the expression of Correspondence to: Professor Weiyuan Zhang, Department of Obstetrics and Gynecology, Beijing Obstetrics and Gynecology protein-coding RNAs via direct binding to these sequences. Hospital, Capital Medical University, 251 Yaojiayuan Road, Similarly to lncRNAs and mRNAs, miRNAs notably influ- Chaoyang, Beijing 100000, P.R. China ence tumor growth, invasion, and migration by acting as either E‑mail: [email protected] oncogenes or tumor suppressor genes, and therefore may influ- ence disease outcome in patients with cancer (6). Key words: long non-coding RNA, microRNA, competing Thus, a large-scale analysis of lncRNA‑miRNA‑mRNA endogenous RNA, cervical cancer, expression profile interactions as a competitive endogenous RNA (ceRNA) network is essential for the comprehensive understanding of the oncogenesis and prognosis of cervical cancer. To date, 406 CHEN et al: RNA BIOINFORMATIC ANALYSIS IN CERVICAL CANCER FROM TCGA DATABASE however, few studies have been published that aimed to eluci- lncRNA‑mRNA pairs: i) the lncRNA and mRNA must share date the association among mRNAs, lncRNAs, and miRNAs a significant number of miRNAs. A hypergeometric test was through a ceRNA network in cervical cancer. used to determine whether a lncRNA and mRNA shared a The Cancer Genome Atlas (TCGA) is a public database significant number of miRNAs. A newly developed algorithm that provides access to genomic data from various types of spongeScan (10) was employed to predict MREs of lncRNAs. cancer (7). In the present study, RNA‑sequencing (RNA‑seq) StarBase v.2.0 (11) was used to retrieve predicted and experi- profiles were retrieved from TCGA to analyze genes that are mentally confirmed miRNA‑mRNA and/or miRNA‑lncRNA dysregulated in cervical cancer. The relationship between interactions. ii) Expression of lncRNA and mRNA must be aberrant RNA expression profiles and overall survival was positively correlated. There have been a number of reports of also analyzed. Moreover, Gene Ontology (GO) and Kyoto miRNAs acting as negative regulators of gene expression. If a Encyclopedia of Genes and Genomes (KEGG) analyses were greater number of miRNAs are occupied by lncRNAs, fewer of conducted to annotate the DEmRNAs. these miRNAs will bind to the target mRNA, thus increasing A total of 255 mRNAs, 15 miRNAs, and 12 lncRNAs the expression level of mRNA. Therefore, expression of were identified as prognostic biomarkers for patients lncRNAs and mRNAs in a ceRNA pair should be positively with cervical cancer. Importantly, a miRNA‑mediated correlated. iii) MiRNAs that share similar sequences should lncRNA‑miRNA‑mRNA ceRNA network was constructed serve similar roles in regulating the expression of lncRNAs and, to the best of the authors' knowledge for the first time, and mRNAs. the lncRNA EPB41L4A‑AS1 was confirmed as a pivotal regu- Two methods were used to determine the regulatory role of lator in cervical carcinoma through bioinformatics analysis. miRNAs in the lncRNAs and mRNAs: Taken together, our results suggest this novel lncRNA is a potential diagnostic biomarker, contributing to our knowledge Regulation similarity. A similarity score was defined to of the interactions between mRNAs and non-coding RNAs in analyze the similarity between miRNA‑lncRNA expression cervical cancer. correlation and miRNA‑mRNA expression correlation. The following formula was used: Materials and methods Materials and data. A total of 307 cases were retrieved from TCGA database, among which 304 were cervical squamous Where M indicates the total number of shared microRNAs, cell carcinoma and endocervical adenocarcinoma (CESC) k stands for the kth shared miRNA, and corr(mk, l) and primary tumor tissues, and three were solid normal tissues. corr(mk, g) represent the Pearson correlation between the RNA expression data, as well as clinical information, were kth miRNA and lncRNA and the kth miRNA and mRNA, obtained from TCGA website (Date of access for database: respectively. 27th August 2018). Note that medical ethics committee approval was not required for the present study. Sensitivity correlation. Sensitivity correlation, previously defined by Paci et al (12), was used to examine whether the Differential gene expression analysis. Linear Models for interaction between mRNA and lncRNA is mediated by Microarray Data (Limma) (8) was used to identify DE miRNA in the lncRNA‑miRNA‑mRNA triplet. The average of genes (DEGs), comparing between primary tumor tissues and all triplets of a lncRNA‑mRNA pair and their shared miRNAs solid normal tissues. The ggplot2 (http://ggplot.yhathq.com/) was considered as the sensitivity relevance between a selected package in R software was employed to generate a volcano mRNA and lncRNA: plot and to perform hierarchical clustering analysis to distin- guish statistically significant DEGs. The selection criteria were P<0.05 and |fold change|>2 for DEGs. Where M indicates the total number of shared miRNAs, Functional enrichment analysis. R package clusterProfiler (9) k stands for the kth shared miRNA, corr(l, g), corr(mk, l), was used to conduct functional enrichment analysis, and and corr(mk, g) represent the Pearson correlation among significant enrichment in GO and KEGG pathways (P<0.01 the lncRNA and the protein coding gene, the kth miRNA and q<0.01) were identified. P‑values were adjusted with the and lncRNA, and the kth miRNA and mRNA, respectively. Benjamini-Hochberg method. A selection of DEGs that were The network was further filtered by hyperP‑value<0.05 and significantly enriched in cell cycle pathways were displayed in corP-value<0.05.
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