MiRNA Synergistic Network Construction and Enrichment Analysis for Common Target Genes in Small-cell Lung Cancer

Zhang, Tie-Feng; Cheng, Ke-Wen; Shi, Wei-Yin; Zhang, Jin-Tao; Liu, Ke-Di; Xu, Shu-Guang; Chen, Ji-Quan

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자료유형: 학술저널

저자정보: Zhang, Tie-Feng (Department of Respiratory Medicine, Shanghai Dachang Hospital) Cheng, Ke-Wen (Department of Respiratory Medicine, Shanghai Renhe Hospital) Shi, Wei-Yin (Department of Respiratory Medicine, Shanghai Dachang Hospital) Zhang, Jin-Tao (Department of Emergency Medicine, Shanghai Dachang Hospital) Liu, Ke-Di (Department of Respiratory Medicine, Shanghai Dachang Hospital) Xu, Shu-Guang (Department of Respiratory Medicine, Shanghai Dachang Hospital) Chen, Ji-Quan (Department of Respiratory Medicine, Shanghai Changzheng Hospital)

저널정보: 아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제13권 제12호

발행연도: 2012.1

수록면: 6,375 - 6,378 (4page)

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Background: Small-cell lung cancer (also known as SCLC) is an aggressive form and untreated patients generally die within about 3 months. To obtain further insight into mechanism underlying malignancy with this cancer, an miRNA synergistic regulatory network was constructed and analyzed in the present study. Method: A miRNA microarray dataset was downloaded from the NCBI GEO database (GSE27435). A total of 546 miRNAs were identified to be expressed in SCLC cells. Then a miRNA synergistic network was constructed, and the included miRNAs mapped to the network. Topology analysis was also performed to analyze the properties of the synergistic network. Consequently, we could identified constitutive modules. Further, common target genes of each module were identified with CFinder. Finally, enrichment analysis was performed for target genes. Results: In this study, a miRNA synergistic network with 464 miRNAs and 2981 edges was constructed. According to the topology analysis, the topological properties between the networks constructed by LC related miRNAs and LC unrelated miRNAs were significantly different. Moreover, a module cilque0 could be identified in our network using CFinder. The module included three miRNAs (hsa-let-7c, hsa-let-7b and hsa-let-7d). In addition, several genes were found which were predicted to be common targets of cilque0. The enrichment analysis demonstrated that these target genes were enriched in MAPK signaling pathways. Conclusions: Although limitations exist in the current data, the results uncovered here are important for understanding the key roles of miRNAs in SCLC. However, further validation is required since our results were based on microarray data derived from a small sample size.

#Small cell lung cancer #mechanism #miRNA synergistic network

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