Luo Tao, Yi Xiangli, Si Wei
Department of Blood Transfusion, Tianjin Hospital, Tianjin 300211, P.R. China.
Department of Intensive Care Unit, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, P.R. China.
Oncol Lett. 2017 Nov;14(5):5427-5433. doi: 10.3892/ol.2017.6845. Epub 2017 Aug 28.
The aim of the present study was to understand the molecular mechanisms of osteosarcoma by comprehensive analysis of microRNA (miRNA/miR) and copy number variation (CNV) microarray data. Microarray data (GSE65071 and GSE33153) were downloaded from the Gene Expression Omnibus. In GSE65071, differentially expressed miRNAs between the osteosarcoma and control groups were calculated by the Limma package. Target genes of differentially expressed miRNAs were identified by the starBase database. For GSE33153, PennCNV software was used to perform the copy number variation (CNV) analysis. Overlapping of the genes in CNV regions and the target genes of differentially expressed miRNAs were used to construct miRNA-gene regulatory network using the starBase database. A total of 149 differentially expressed miRNAs, including 13 downregulated and 136 upregulated, were identified. In the GSE33153 dataset, 987 CNV regions involving in 3,635 genes were identified. In total, 761 overlapping genes in 987 CNV regions and in the genes in 7,313 miRNA-gene pairs were obtained. miRNAs (hsa-miR-27a-3p, hsa-miR-124-3p, hsa-miR-9-5p, hsa-miR-182-5p, hsa-miR-26a-5p) and the genes [Fibroblast growth factor receptor substrate 2 (), coronin 1C (), forkhead box P1 (), cytoplasmic polyadenylation element binding protein 4 () and glucocorticoid induced 1 ()] with the highest degrees of association with osteosarcoma development were identified. Hsa-miR-27a-3p, hsa-miR-9-5p, hsa-miR-182-5p, , , and may be involved in osteosarcoma pathogenesis, and development.
本研究的目的是通过对微小RNA（miRNA/miR）和拷贝数变异（CNV）微阵列数据的综合分析来了解骨肉瘤的分子机制。微阵列数据（GSE65071和GSE33153）从基因表达综合数据库下载。在GSE65071中，通过Limma软件包计算骨肉瘤组和对照组之间差异表达的miRNA。通过starBase数据库鉴定差异表达miRNA的靶基因。对于GSE33153，使用PennCNV软件进行拷贝数变异（CNV）分析。利用starBase数据库，将CNV区域中的基因与差异表达miRNA的靶基因进行重叠分析，构建miRNA-基因调控网络。共鉴定出149个差异表达的miRNA，其中13个下调，136个上调。在GSE33153数据集中，鉴定出涉及3635个基因的987个CNV区域。总共获得了987个CNV区域中的761个重叠基因以及7313个miRNA-基因对中的基因。鉴定出与骨肉瘤发生发展关联度最高的miRNA（hsa-miR-27a-3p、hsa-miR-124-3p、hsa-miR-9-5p、hsa-miR-182-5p、hsa-miR-26a-5p）和基因[成纤维细胞生长因子受体底物2（）、冠蛋白1C（）、叉头框P1（）、细胞质聚腺苷酸化元件结合蛋白4（）和糖皮质激素诱导蛋白1（）]。Hsa-miR-27a-3p、hsa-miR-9-5p、hsa-miR-182-5p、、、和可能参与骨肉瘤的发病机制和发展。
