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Ren et al. Journal of Orthopaedic Surgery and Research (2018) 13:153 https://doi.org/10.1186/s13018-018-0860-8 RESEARCHARTICLE Open Access Exploring the key genes and pathways of side population cells in human osteosarcoma using gene expression array analysis Yi-Ming Ren†, Yuan-Hui Duan†, Yun-Bo Sun†, Tao Yang, Wen-Jun Zhao, Dong-Liang Zhang, Zheng-Wei Tian and Meng-Qiang Tian* Abstract Background: Human osteosarcoma (OS) is one of the most common primary bone sarcoma, because of early metastasis and few treatment strategies. It has been reported that the tumorigenicity and self-renewal capacity of side population (SP) cells play roles in human OS via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) that regulated between the SP cells and the non-SP cells from primary human OS and identify their functions and molecular pathways associated with OS. Methods: The gene expression profile GSE63390 was downloaded, and bioinformatics analysis was made. Results: One hundred forty-one DEGs totally were identified. Among them, 72 DEGs (51.06%) were overexpressed, and the remaining 69 DEGs (48.94%) were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene–gene interaction network analysis such as EIF4E, FAU, HSPD1, IL-6, and KISS1, which may have a relationship with the development process of OS. We also discovered that EIF4E/mTOR signaling pathway could be a potential research target for therapy and tumorigenesis of OS. Conclusion: This analysis provides a comprehensive understanding of the roles of DEGs coming from SP cells in the development of OS. However, these predictions need further experimental validation in future studies. Keywords: Osteosarcoma, Side population cells, Differentially expressed genes, Bioinformatics analysis Background treatment of OS are the breakthrough point of OS Osteosarcoma (OS), which is produced by mesenchymal research and clinical application, and exploring the cells, is the most common primary malignant tumor pathogenesis, development, and metastasis of OS is the originating from bone tissues. OS occurs mainly in key. Although a large number of studies have been made children and adolescents and accounts for 8.9% of on OS at molecular and cellular levels, the mechanisms cancer-related diseases which lead to death [1, 2]. Al- of OS formation and metastasis have not been fully though new therapies of neoadjuvant chemotherapy and elucidated. surgery have contributed greatly to OS treatment, the Side population (SP) cells are a group of special cells, 5-year survival rate of OS is difficult to exceed 60–65% which were found when Hoechst and flow cytometry are [3, 4]. To sum up, the early diagnosis and effective used to separate hematopoietic stem cells and progenitor cells. SP cells are widely distributed in a variety of adult * Correspondence: [email protected] tissues, embryos, and some tumor cell lines [5]. They †Yi-Ming Ren, Yuan-Hui Duan and Yun-Bo Sun contributed equally to this work. not only have self-renewal and multipotential differenti- Department of Joint and Sport Medicine, Tianjin Union Medical Center, ation potential, but also have unique phenotypic markers Jieyuan Road 190, Hongqiao District, Tianjin 300121, People’s Republic of and biological characteristics of stem cells, whose China © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Ren et al. Journal of Orthopaedic Surgery and Research (2018) 13:153 Page 2 of 10 characteristics are very similar to those of tumor stem GO and KEGG analysis of DEGs cells [6, 7]. SP cells help maintain the tumorigenic Target genes list were submitted to the Cytoscape software potential of some tumor cell lines [8–10]. Ho et al. re- version 3.4.0 (www.cytoscape.org)andClueGOversion ported that SP cells were enriched in tumor-initiating 2.33 to identify overrepresented GO categories and pathway capability compared with non-SP cells by nonobese categories. Gene Ontology (GO) analysis was used to pre- diabetic/severe combined immunodeficiency xenograft dict the potential functions of the DEGs in biological experiments. Matrigel invasion assay showed that SP process (BP), molecular function (MF), and cellular compo- cells also have higher potential for invasiveness. Human nent (CC). The Kyoto Encyclopedia of Genes and Genomes telomerase reverse transcriptase expression was higher (KEGG, http://www.genome.jp/)isaknowledgebasefor in the SP cells, suggesting that this fraction may repre- systematic analysis of gene functions, linking genomic in- sent a reservoir with unlimited proliferative potential for formation with higher-level systemic functions. Finally, the generating cancer cells [11]. Chiba et al. hold that a mi- overrepresented pathway categories with a P value < 0.05 nority population of SP cells detected in hepatocellular were considered statistically significant using KEGG carcinoma cells possessed extreme tumorigenic potential pathway enrichment analysis. and provided heterogeneity to the cancer stem cell sys- tem characterized by distinct hierarchy [12]. Wang et al. Gene interaction network construction observed a strong tumorigenesis ability of SP cells from A large number of DEGs we obtained may be human HeLa cell line following in vivo transplantation into 5- OS-associated genes, and it is suggested that these DEGs to 6-week-old female Balb/c mice [13]. These findings in SP cells may participate in the progression of human indicate that SP cells is an enriched source of OS. Firstly, DEGs list was submitted to the Search Tool tumor-initiating cells with stem cell properties and may for the Retrieval of Interacting Genes (STRING) be an important target for effective therapy and a useful database (http://www.string-db.org/) and an interaction tool to investigate the tumorigenic process. network chart with a combined score > 0.4 was saved Interestingly, SP cells are present in primary mesen- and exported. Subsequently, the interaction regulatory chymal neoplasms, including primary OS [14]. Here, we network of human OS-associated genes was visualized downloaded the gene expression profile GSE63390 from using Cytoscape software version 3.4.0. The distribution the Gene Expression Omnibus (GEO) database and of core genes in the interaction network was made by made bioinformatics analysis to investigate differentially NetworkAnalyzer in Cytoscape. Then, the plugin expressed genes (DEGs) that regulated between the SP Molecular Complex Detection (MCODE) was applied to cells and the non-SP cells from primary human OS. By screen the modules of the gene interaction network in doing this, we hope that the key target genes and path- Cytoscape. ways involved in the carcinogenesis and progression of human OS could be identified and existing molecular Results mechanisms could be revealed. Identification of DEGs The gene expression profile GSE63390 was downloaded Methods from the GEO, and the GEO2R method was used to Gene expression microarray data identify DEGs in SP cells compared with non-SP cells. P The gene expression profile GSE63390 was downloaded value < 0.05, log FC > 1.0, or log FC < − 1.0 were used as from the Gene Expression Omnibus (GEO, www.ncbi.nlm.- the cut-off criteria. After analyzing, differentially expres- nih.gov/geo/). GSE63390 was based on Illumina Human sion gene profiles were obtained. Totally, 141 DEGs HT-12 V4.0 expression beadchip GPL10558 platform. The were identified including 72 upregulated DEGs and 69 GSE63390 dataset contained three samples, including three downregulated DEGs screened in SP cells of human OS SP cell samples and three non-SP cell samples. compared with non-SP cells. Parts of DEGs were listed in Table 1. DEGs in SP cells and non-SP cells The raw data files used for the analysis included TXT GO term enrichment analysis of DEGs files (Illumina platform). The analysis was carried out Functional annotation of the 141 DEGs was clarified using GEO2R, which can perform comparisons on ori- using the Cytoscape software online tool. GO analysis ginal submitter-supplied processed data tables using the indicated that these DEGs were significantly enriched in GEO query and limma R packages from Bioconductor cellular amide metabolic process, peptide metabolic project. The P value < 0.05 and log fold change (FC) > process, translation, translational initiation, selenium 1.0 or log FC < − 1.0 were used as the cut-off criteria. compound metabolic process, cellular modified amino The DEGs with statistical significance between the SP acid metabolic process, aromatic compound catabolic cells and non-SP cells were selected and identified. process, cellular nitrogen compound catabolic process, Ren et al. Journal of Orthopaedic Surgery and Research (2018) 13:153 Page 3 of 10 Table 1 The top 10 regulated DEGs in OS SP cells with P value NOD-like receptor signaling pathway, apelin signaling < 0.05 pathway, ECM–receptor interaction, Toll-like receptor ID P value logFC Gene symbol signaling pathway, mTOR signaling pathway, FoxO Upregulated signaling pathway, cell adhesion molecules (CAMs) and ILMN_2184250 6.45E−05 3.0817572 SERPINB9 hedgehog signaling pathway, and others. These key pathways were showed in Fig. 2. Fifty-five nodes and 163 ILMN_1713706 4.08E−02 3.08089766 ZNF786 edges could be discovered in this network. FoxO signal- − ILMN_2260756 4.98E 02 2.76569527 GSDMB ing pathway and mTOR signaling pathway clustered to- ILMN_2189870 3.65E−03 2.52175439 FCF1 gether. Estrogen signaling pathway and hippo signaling ILMN_2078724 2.68E−02 2.46037207 APOPT1 pathway clustered together.
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