Exploration of Molecular Mechanisms of Diffuse Large B-cell Lymphoma Development Using a Microarray
| Autor: | Cui-Fen Shen, Li-Hong Shou, Hui-Ying Zhang, Zong-Xin Zhang, Wen-Jun Jin, Wei-Hua Zou |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Cancer Research
Cell signaling Microarray Epidemiology Biology Interaction network Gene expression Biomarkers Tumor medicine Humans Gene Regulatory Networks KEGG Oligonucleotide Array Sequence Analysis Genetics Microarray analysis techniques Gene Expression Profiling Public Health Environmental and Occupational Health Computational Biology Microarray Analysis Prognosis medicine.disease Gene Expression Regulation Neoplastic Oncology Case-Control Studies Gene chip analysis Lymphoma Large B-Cell Diffuse Diffuse large B-cell lymphoma Signal Transduction |
| Zdroj: | Asian Pacific Journal of Cancer Prevention. 14:1731-1735 |
| ISSN: | 1513-7368 |
| DOI: | 10.7314/apjcp.2013.14.3.1731 |
| Popis: | Objective: We aimed to identify key genes, pathways and function modules in the development of diffuse large B-cell lymphoma (DLBCL) with microarray data and interaction network analysis. Methods: Microarray data sets for 7 DLBCL samples and 7 normal controls was downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified with Student’s t-test. KEGG functional enrichment analysis was performed to uncover their biological functions. Three global networks were established for immune system, signaling molecules and interactions and cancer genes. The DEGs were compared with the networks to observe their distributions and determine important key genes, pathways and modules. Results: A total of 945 DEGs were obtained, 272 up-regulated and 673 down-regulated. KEGG analysis revealed that two groups of pathways were significantly enriched: immune function and signaling molecules and interactions. Following interaction network analysis further confirmed the association of DEGs in immune system, signaling molecules and interactions and cancer genes. Conclusions: Our study could systemically characterize gene expression changes in DLBCL with microarray technology. A range of key genes, pathways and function modules were revealed. Utility in diagnosis and treatment may be expected with further focused research. |
| Databáze: | OpenAIRE |
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