Bioinformatics Analysis Identifies the Estrogen Receptor 1 (ESR1) Gene and hsa-miR-26a-5p as Potential Prognostic Biomarkers in Patients with Intrahepatic Cholangiocarcinoma

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Abstract

Background

Intrahepatic cholangiocarcinoma arises from the epithelial cells of the bile ducts and is associated with poor prognosis. This study aimed to use bioinformatics analysis to identify molecular biomarkers of intrahepatic cholangiocarcinoma and their potential mechanisms.

Material/Methods

MicroRNA (miRNA) and mRNA microarrays from GSE53870 and GSE32879 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEMs) associated with prognosis were identified using limma software and Kaplan-Meier survival analysis. Predictive target genes of the DEMs were identified using miRWalk, miRTarBase, miRDB, and TargetScan databases of miRNA-binding sites and targets. Target genes underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Hub genes were analyzed by constructing the protein-protein interaction (PPI) network using Cytoscape. DEMs validated the hub genes, followed by construction of the miRNA-gene regulatory network.

Results

Twenty-five DEMs were identified. Fifteen DEMs were upregulated, and ten were down-regulated. Kaplan-Meier survival analysis identified seven upregulated DEMs and nine down-regulated DEMs that were associated with the overall survival (OS), and 130 target genes were selected. GO analysis showed that target genes were mainly enriched for metabolism and development processes. KEGG analysis showed that target genes were mainly enriched for cancer processes and some signaling pathways. Fourteen hub genes identified from the PPI network were associated with the regulation of cell proliferation. The overlap between hub genes and DEMs identified the estrogen receptor 1 (ESR1) gene and hsa-miR-26a-5p.

Conclusions

Bioinformatics analysis identified ESR1 and hsa-miR-26a-5p as potential prognostic biomarkers for intrahepatic cholangiocarcinoma.

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Most cited references 67

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Gene Ontology: tool for the unification of biology

Michael Ashburner, Catherine A. Ball, Judith Blake … (2003)

Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

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miRDB: an online resource for microRNA target prediction and functional annotations

Nathan C. Wong, Xiaowei Wang (2014)

MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.

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miRWalk: An online resource for prediction of microRNA binding sites

Carsten Sticht, Carolina de la Torre, Alisha Parveen … (2018)

miRWalk is an open-source platform providing an intuitive interface that generates predicted and validated miRNA-binding sites of known genes of human, mouse, rat, dog and cow. The core of miRWalk is the miRNA target site prediction with the random-forest-based approach software TarPmiR searching the complete transcript sequence including the 5’-UTR, CDS and 3’-UTR. Moreover, it integrates results other databases with predicted and validated miRNA-target interactions. The focus is set on a modular design and extensibility as well as a fast update cycle. The database is available using Python, MySQL and HTML/Javascript Database URL: http://mirwalk.umm.uni-heidelberg.de.

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Author and article information

Journal

Journal ID (nlm-ta): Med Sci Monit

Journal ID (iso-abbrev): Med. Sci. Monit

Journal ID (publisher-id): Medical Science Monitor

Title: Medical Science Monitor : International Medical Journal of Experimental and Clinical Research

Publisher: International Scientific Literature, Inc.

ISSN (Print): 1234-1010

ISSN (Electronic): 1643-3750

Publication date Collection: 2020

Publication date (Electronic): 21 May 2020

Publication date (Electronic preprint): 26 March 2020

Volume: 26

Pages: e921815-1-e921815-15

Affiliations

Queen Mary School of Nanchang University, Nanchang, Jiangxi, P.R. China

Author notes

Corresponding Authors: Xianzheng Qin, e-mail: jp6303416178@ 123456qmul.ac.uk , Yuning Song, e-mail jp6303416179@ 123456qmul.ac.uk

[A]

Study Design

[B]

Data Collection

[C]

Statistical Analysis

[D]

Data Interpretation

[E]

Manuscript Preparation

[F]

Literature Search

[G]

Funds Collection

[*]

Xianzheng Qin and Yuning Song contributed equally to this work

Article

Publisher ID: 921815

DOI: 10.12659/MSM.921815

PMC ID: 7257878

PubMed ID: 32435051

SO-VID: a2b34620-4745-4c8c-8829-cb0eef877f96

License:

This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International ( CC BY-NC-ND 4.0)

Bioinformatics Analysis Identifies the Estrogen Receptor 1 (ESR1) Gene and hsa-miR-26a-5p as Potential Prognostic Biomarkers in Patients with Intrahepatic Cholangiocarcinoma

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Abstract

Background

Material/Methods

Results

Conclusions

Related collections

Core Readings in Statistical Mediation Analysis

Most cited references 67

Gene Ontology: tool for the unification of biology

miRDB: an online resource for microRNA target prediction and functional annotations

miRWalk: An online resource for prediction of microRNA binding sites

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