Identifying osteosarcoma metastasis associated genes by weighted gene co-expression network analysis (WGCNA)
| Autor: | Donghui Guan, Jianmin Li, Honglai Tian |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
weighted gene co-expression network analysis Bone Neoplasms Computational biology Metastasis 03 medical and health sciences 0302 clinical medicine Quality Improvement Study Databases Genetic metastasis Humans Medicine Neoplasm Metastasis KEGG Gene Regulation of gene expression Osteosarcoma Mechanism (biology) business.industry Gene Expression Profiling General Medicine medicine.disease Gene Expression Regulation Neoplastic Gene Ontology 030104 developmental biology 030220 oncology & carcinogenesis ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Gene co-expression network Biomarker (medicine) business Research Article |
| Zdroj: | Medicine |
| ISSN: | 0025-7974 |
| DOI: | 10.1097/md.0000000000010781 |
| Popis: | Supplemental Digital Content is available in the text Osteosarcoma (OS), the most common malignant bone tumor, accounts for the heavy healthy threat in the period of children and adolescents. OS occurrence usually correlates with early metastasis and high death rate. This study aimed to better understand the mechanism of OS metastasis. Based on Gene Expression Omnibus (GEO) database, we downloaded 4 expression profile data sets associated with OS metastasis, and selected differential expressed genes. Weighted gene co-expression network analysis (WGCNA) approach allowed us to investigate the most OS metastasis-correlated module. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to give annotation of selected OS metastasis-associated genes. We select 897 differential expressed genes from OS metastasis and OS non-metastasis groups. Based on these selected genes, WGCNA further explored 142 genes included in the most OS metastasis-correlated module. Gene Ontology functional and KEGG pathway enrichment analyses showed that significantly OS metastasis-associated genes were involved in pathway correlated with insulin-like growth factor binding. Our research figured out several potential molecules participating in metastasis process and factors acting as biomarker. With this study, we could better explore the mechanism of OS metastasis and further discover more therapy targets. |
| Databáze: | OpenAIRE |
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