Abnormal DNA methylation may contribute to the progression of osteosarcoma

Chen,Xiao‑Gang; Ma,Liang; Xu,Jia‑Xin

doi:10.3892/mmr.2017.7869

Abnormal DNA methylation may contribute to the progression of osteosarcoma

Authors:
- Xiao‑Gang Chen
- Liang Ma
- Jia‑Xin Xu
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Affiliations: Department of Orthopedic Surgery, The People's Hospital of Baoan Shenzhen, Shenzhen, Guangdong 518101, P.R. China, Department of Orthopedics, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250011, P.R. China, Department of Spine Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China
Published online on: October 25, 2017 https://doi.org/10.3892/mmr.2017.7869
Pages: 193-199
Copyright: © Chen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The identification of optimal methylation biomarkers to achieve maximum diagnostic ability remains a challenge. The present study aimed to elucidate the potential molecular mechanisms underlying osteosarcoma (OS) using DNA methylation analysis. Based on the GSE36002 dataset obtained from the Gene Expression Omnibus database, differentially methylated genes were extracted between patients with OS and controls using t‑tests. Subsequently, hierarchical clustering was performed to segregate the samples into two distinct clusters, OS and normal. Gene Ontology (GO) and pathway enrichment analyses for differentially methylated genes were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein‑protein interaction (PPI) network was established, followed by hub gene identification. Using the cut‑off threshold of ≥0.2 average β‑value difference, 3,725 unique CpGs (2,862 genes) were identified to be differentially methylated between the OS and normal groups. Among these 2,862 genes, 510 genes were differentially hypermethylated and 2,352 were differentially hypomethylated. The differentially hypermethylated genes were primarily involved in 20 GO terms, and the top 3 terms were associated with potassium ion transport. For differentially hypomethylated genes, GO functions principally included passive transmembrane transporter activity, channel activity and metal ion transmembrane transporter activity. In addition, a total of 10 significant pathways were enriched by differentially hypomethylated genes; notably, neuroactive ligand‑receptor interaction was the most significant pathway. Based on a connectivity degree >90, 7 hub genes were selected from the PPI network, including neuromedin U (NMU; degree=103) and NMU receptor 1 (NMUR1; degree=103). Functional terms (potassium ion transport, transmembrane transporter activity, and neuroactive ligand‑receptor interaction) and hub genes (NMU and NMUR1) may serve as potential targets for the treatment and diagnosis of OS.

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