Investigation of crucial genes and microRNAs in conventional osteosarcoma using gene expression profiling analysis

Peng,Chuangang; Yang,Qi; Wei,Bo; Yuan,Baoming; Liu,Yong; Li,Yuxiang; Gu,Dawer; Yin,Guochao; Wang,Bo; Xu,Dehui; Zhang,Xuebing; Kong,Daliang

doi:10.3892/mmr.2017.7506

Investigation of crucial genes and microRNAs in conventional osteosarcoma using gene expression profiling analysis

Authors:
- Chuangang Peng
- Qi Yang
- Bo Wei
- Baoming Yuan
- Yong Liu
- Yuxiang Li
- Dawer Gu
- Guochao Yin
- Bo Wang
- Dehui Xu
- Xuebing Zhang
- Daliang Kong
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Affiliations: Orthopaedic Medical Center, The 2nd Hospital of Jilin University, Changchun, Jilin 130041, P.R. China, Department of Gynecology and Obstetrics, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Orthopaedics, Jilin Oilfield General Hospital, Songyuan, Jilin 131200, P.R. China, Department of Orthopaedics, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China
Published online on: September 18, 2017 https://doi.org/10.3892/mmr.2017.7506
Pages: 7617-7624

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Abstract

The present study aimed to screen potential genes associated with conventional osteosarcoma (OS) and obtain further information on the pathogenesis of this disease. The microarray dataset GSE14359 was downloaded from the Gene Expression Omnibus. A total of 10 conventional OS samples and two non‑neoplastic primary osteoblast samples in the dataset were selected to identify the differentially expressed genes (DEGs) using the Linear Models for Microarray Data package. The potential functions of the DEGs were predicted using Gene Ontology (GO) and pathway enrichment analyses. Protein‑protein interaction (PPI) data were also obtained using the Search Tool for the Retrieval of Interacting Genes database, and the PPI network was visualized using Cytoscape. Module analysis was then performed using the Molecular Complex Detection module. Additionally, the potential microRNAs (miRNAs) for the upregulated DEGs in the most significant pathway were predicted using the miRDB database, and the regulatory network for the miRNAs‑DEGs was visualized in Cytoscape. In total, 317 upregulated and 670 downregulated DEGs were screened. Certain DEGs, including cyclin‑dependent kinase 1 (CDK1), mitotic arrest deficient 2 like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine‑protein kinase (BUB1), were significantly enriched in the cell cycle phase and oocyte meiosis pathway. DEGs, including replication factor C subunit 2 (RFC2), RFC3, RFC4 and RFC5, were significantly enriched in DNA replication and interacted with each other. RFC4 also interacted with other DEGs, including CDK1, MAD2L1, NDC80 kinetochore complex and BUB1. In addition, RFC4, RFC3 and RFC5 were targeted by miRNA (miR)‑802, miR‑224‑3p and miR‑522‑3p. The DEGs encoding RFC may be important for the development of conventional OS, and their expression may be regulated by a number of miRNAs, including miR‑802, miR‑224‑3p and miR‑522‑3p.

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