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Screening feature genes of osteosarcoma with DNA microarray: a bioinformatic analysis.


ABSTRACT: To screen differentially expressed genes (DEGs) of Osteosarcoma (OS) by using the microarray expression profiles of tissues of normal person and patients with OS for early diagnosis and effective treatment of OS. We downloaded the gene expression profile of GES16088 from Gene Expression Omnibus database, including twenty samples from fourteen patients diagnosed with osteosarcoma and six normal samples as control groups. We identified the DEGs by Affy package in R language. Bioinformatic methods were used for further analysis of the screened DEGs. Firstly, cluster analysis was performed on the selected DEGs for comparison of the expression degree. After protein-protein interaction (PPI) network of differentially expressed genes was constructed by STRING, we analyzed gene functions with DAVID and WebGestalt. Compared with the control, we screened three distinctly up-regulated genes. These DEGs had close relationship with transmission signaling pathway, organ and system development. The up-regulated gene COL was the most representative genes among the DEGs. The screened DEGs have a great significance on studying mechanism of osteosarcoma. It might distinguish normal and pathological tissues of OS and thus become target genes for monitoring, diagnosis and treatment of the OS. It has the potential to use in clinic.

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC4509196 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Screening feature genes of osteosarcoma with DNA microarray: a bioinformatic analysis.

Zhang Yunpeng Y   Yan Shi S   Lu Daifeng D   Dong Feng F   Lian Yongyun Y  

International journal of clinical and experimental medicine 20150515 5


To screen differentially expressed genes (DEGs) of Osteosarcoma (OS) by using the microarray expression profiles of tissues of normal person and patients with OS for early diagnosis and effective treatment of OS. We downloaded the gene expression profile of GES16088 from Gene Expression Omnibus database, including twenty samples from fourteen patients diagnosed with osteosarcoma and six normal samples as control groups. We identified the DEGs by Affy package in R language. Bioinformatic methods  ...[more]

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