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Erschienen in: Pathology & Oncology Research 2/2020

09.07.2019 | Original Article

Molecular Network-Based Identification of Circular RNA-Associated ceRNA Network in Papillary Thyroid Cancer

verfasst von: Qin Liu, Liang-zhi Pan, Min Hu, Jian-ying Ma

Erschienen in: Pathology & Oncology Research | Ausgabe 2/2020

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Abstract

Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. Nevertheless, their function and underlying mechanisms in papillary thyroid cancer (PTC) remains largely unknown. This study aimed to describe the regulatory mechanisms in PTC. The expression profile of circRNA was download from the Gene Expression Omnibus (GEO) database. The mRNA and miRNA data of PTC was downloaded from The Cancer Genome Atlas (TCGA) database. The circRNA-miRNA-mRNA network by Cytoscape. The interactions between proteins were analyzed using the STRING database and hubgenes were identified using MCODE plugin. Then, we conducted a circRNA-miRNA-hubgenes regulatory module. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway analysis were conducted using R packages “Clusterprofile”. We identified 14 differential expression circRNAs (DEcircRNA), 3106 differential expression mRNAs (DEmRNA), 142 differential expression miRNAs (DEmiRNA) and in PTC. Twelve circRNAs, 33 miRNAs, and 356 mRNAs were identified to construct the ceRNA network of PTC. PPI network and module analysis identified 5 hubgenes. Then, a circRNA-miRNA-hubgene subnetwork was constructed based on the 2 DEcircRNAs, 3 DEmiRNAs, and 4 DEmRNAs. GO and KEGG pathway analysis indicated DEmRNAs might be associated with PTC onset and progression. These ceRNAs are critical in the pathogenesis of PTC and may serve as future therapeutic biomarkers.
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Metadaten
Titel
Molecular Network-Based Identification of Circular RNA-Associated ceRNA Network in Papillary Thyroid Cancer
verfasst von
Qin Liu
Liang-zhi Pan
Min Hu
Jian-ying Ma
Publikationsdatum
09.07.2019
Verlag
Springer Netherlands
Erschienen in
Pathology & Oncology Research / Ausgabe 2/2020
Print ISSN: 1219-4956
Elektronische ISSN: 1532-2807
DOI
https://doi.org/10.1007/s12253-019-00697-y

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