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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/10927

    Title: A Gene Chip Approach to Anti-cancer Effect of Tien-Shen Lingzhi Ethanol Extracts on Non-Small Cell Lung Cancer Cell Line
    Authors: Hui-Hsia Hsieh
    Contributors: Department of Bioinformatics
    Keywords: Tien-Shen Lingzhi;Ganoderma tsugae;Microarray;Lung Cancer;Cell Cycle
    Date: 2010
    Issue Date: 2010-11-08 10:33:19 (UTC+8)
    Publisher: Asia University
    Abstract: Background: Lung cancers are among the neoplastic diseases with the worst prognosis. More treatment modalities are needed to improve clinical outcome. It’s being a new trend to search for bioactive traditional Chinese medicines (TCM). Ganoderma, also known as Lingzhi, is a TCM and has been widely used for improving human health for centuries. We have addressed the anticancer effects of Ganoderma on various cancers. In this study, a comprehensive genomic profiling was used to further explore the signal pathway for the anticancer effects of Tien Shen Lingzhi(TSL),an improved strain of Ganoderma tsugae. Methods: A comparative genomics study was performed to search for TSL-mediated differential expressions on H23/0.3 cells. Bioinformatics tool, e.g., GeneGo Meta CoreTM ,was used to analyze the experimental results based on Affymetrix Human Genome U133 Plus 2.0 microarray. Results: The whole-genome expression profiles of H23/0.3 with or without TSL treatment were resolved by multidimentional scaling (MDS) analysis. It indicated a TSL-mediated cell cycle perturbation. Bioinformatics analysis showed cell cycle was the most affected pathway. GeneGo Meta CoreTM derived cellular pathway map revealed dramatic hits (17/26) on the signal transduction of DNA replication. The microarray results were confirmed by Q-PCR. Conclusion: The genomic microarray data demonstrates the TSL-induced cell cycle deregulation in H23/0.3 cells. TSL-mediated cell cycle perturbation on H23/0.3 cells is consistent with the cellular pathway map resulting from GeneGo Meta CoreTM analysis.
    Appears in Collections:[生物資訊與醫學工程學系 ] 博碩士論文

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