博碩士論文 982213011 詳細資訊




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姓名 劉靜汝(Jing-ru Liu)  查詢紙本館藏   畢業系所 系統生物與生物資訊研究所
論文名稱 利用微陣列資料分析在肝癌的轉錄調控因子
(Analysis of Transcription Factors in Liver Cancer Using Microarray Data)
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摘要(中) 在台灣肝癌是癌症死亡率中最主要死亡疾病。分析基因調控機制可以幫助我們了解肝癌。基因調控分析是利用高通量實驗方法如微陣列晶片和系統生物來分析。雖然微陣列晶片技術可以產生全基因的基因表現量資料,卻仍然受限於樣本數量和晶片成本。統計方法可以挑選在正常細胞和癌細胞中有差異表現量的基因,但仍受限於晶片數量。此外分析共同調控的轉錄因子也是必要的。
在這個研究裡,我們嘗試結合多種微陣列晶片及利用統計方法整合晶片。首先,我們挑選相似的肝癌微陣列晶片。再來,我們嘗試組合不同的實驗室晶片並建立統計模型。最後,我們嘗試分析轉錄調控因子找尋在所有實驗裡可能和肝癌相關的轉錄因子。雖然整合晶片會包含大量的雜訊,但也會增加晶片的數量。如果晶片的數量夠大,對調控分析的基因仍然會好。我們開發一個系統可以結合不同的晶片及分析在基因群上的共同調控轉錄因子。結果證明,我們的基因表單與目前已知的肝癌相關基因是一致的。也證明還有很多和肝癌調控相關的基因和轉錄調控因子是可以被驗證的。
摘要(英) Liver cancer is the mostly death disease of cancer mortality in Taiwan. Analysis of gene regulation mechanism can help us understand in liver cancer. State of art gene regulation analysis uses high-throughput experiment method such as Microarray and system biology in analysis. Although microarray technology can generate gene expressions data of whole genome, the analysis still limited in sample number and array cost. Statistics can select genes that express differently between normal tissue and tumor tissue but will still limited in number of chips. Furthermore, analysis of common transcription factors regulated is also needed.
In this work, we try to integrate multiple microarray chips and use statistic methods on the integrated data. First, we select similar liver cancer microarray experiments. Next, we try to integrate different array serious and establish statistic model. Last, we try to do transcription factor analysis to find possible TF related to liver cancer across all array serious selected. Though the integration will include huge amount of noise, it will also increase the chip number. If the chip number large enough, the gene list will still be good enough for regulation analysis. We develop a computer system which can join multiple chips and analysis the common transcription factors on those genes. Result shows that our gene list consistent with current known cancer related genes. Our result also shows lots of possible liver cancer related gene and transcription factors which can be later be verified.
關鍵字(中) ★ 轉錄因子
★ 肝癌
★ 微陣列晶片
關鍵字(英) ★ Hepatocellular carcinoma
★ microarray
★ transcription factor
論文目次 摘要................................................................................................................................. i
Abstract .......................................................................................................................... ii
誌謝.............................................................................................................................. iii
List of Figures ................................................................................................................ v
List of Tables ................................................................................................................. vi
Chapter1 Introduction ............................................................................................ 1
1.1 Background ............................................................................................ 1
1.2 Motivation .............................................................................................. 3
1.3 Goals ...................................................................................................... 3
Chapter2 Related Works ........................................................................................ 4
2.1 Transcriptional Regulatory Sites............................................................ 4
2.2 Phylogenetic Footprinting ...................................................................... 5
Chapter 3 Materials and Methods ......................................................................... 6
3.1 Materials ................................................................................................ 6
3.1.1 Human Promoter Sequence............................................................ 6
3.1.2 Gene Expression Omnibus ............................................................. 7
3.1.2.1 Affymetrix GeneChip ........................................................... 10
3.1.3 Transcription Factor Binding Site ................................................ 11
3.1.4 Promoter Conserved Region Across Species ............................... 12
3.2 Methods................................................................................................ 13
3.2.1 RMA ............................................................................................ 14
3.2.3 T-test ............................................................................................. 14
Chapter4 Implementation .................................................................................... 16
4.1 System Flow......................................................................................... 16
4.2 Known Liver cancer related gene ........................................................ 17
4.3 Case study ............................................................................................ 17
Chapter5 Discussion ............................................................................................ 25
Reference ..................................................................................................................... 27
Appendix ...................................................................................................................... 30
參考文獻 [1] A. M. Di Bisceglie, "Hepatocellular carcinoma: molecular biology of its growth and relationship to hepatitis B virus infection," Med Clin North Am, vol. 73, pp. 985-97, Jul 1989.
[2] "Hepatocellular carcinoma - United States, 2001-2006," MMWR Morb Mortal Wkly Rep, vol. 59, pp. 517-20, May 7 2010.
[3] T. Tanaka, et al., "Oligonucleotide-arrayed TFT photosensor applicable for DNA chip technology," Biotechnol Bioeng, vol. 95, pp. 22-8, Sep 5 2006.
[4] J. R. Pollack, "DNA microarray technology. Introduction," Methods Mol Biol, vol. 556, pp. 1-6, 2009.
[5] A. P. Tsou, et al., "Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data," IEEE Trans Inf Technol Biomed, vol. 10, pp. 550-8, Jul 2006.
[6] H. D. Huang, et al., "Identifying transcriptional regulatory sites in the human genome using an integrated system," Nucleic Acids Res, vol. 32, pp. 1948-56, 2004.
[7] D. Boffelli, et al., "Phylogenetic shadowing of primate sequences to find functional regions of the human genome," Science, vol. 299, pp. 1391-4, Feb 28 2003.
[8] D. Smedley, et al., "BioMart--biological queries made easy," BMC Genomics, vol. 10, p. 22, 2009.
[9] S. Haider, et al., "BioMart Central Portal--unified access to biological data," Nucleic Acids Res, vol. 37, pp. W23-7, Jul 1 2009.
[10] Y. S. Long, et al., "Human transcription factor genes involved in neuronal development tend to have high GC content and CpG elements in the proximal promoter region," J Genet Genomics, vol. 38, pp. 157-63, Apr 20 2011.
[11] R. Edgar, et al., "Gene Expression Omnibus: NCBI gene expression and hybridization array data repository," Nucleic Acids Res, vol. 30, pp. 207-10, Jan 1 2002.
[12] Y. L. Liao, et al., "Identification of SOX4 target genes using phylogenetic footprinting-based prediction from expression microarrays suggests that overexpression of SOX4 potentiates metastasis in hepatocellular carcinoma," Oncogene, vol. 27, pp. 5578-89, Sep 18 2008.
[13] E. Wurmbach, et al., "Genome-wide molecular profiles of HCV-induced dysplasia and hepatocellular carcinoma," Hepatology, vol. 45, pp. 938-47, Apr 2007.
[14] C. Cillo, et al., "The HOX gene network in hepatocellular carcinoma," Int J Cancer, Jan 20 2011.
28
[15] M. J. Perugorria, et al., "Wilms' tumor 1 gene expression in hepatocellular carcinoma promotes cell dedifferentiation and resistance to chemotherapy," Cancer Res, vol. 69, pp. 1358-67, Feb 15 2009.
[16] V. R. Mas, et al., "Genes involved in viral carcinogenesis and tumor initiation in hepatitis C virus-induced hepatocellular carcinoma," Mol Med, vol. 15, pp. 85-94, Mar-Apr 2009.
[17] K. J. Archer, et al., "Identifying genes for establishing a multigenic test for hepatocellular carcinoma surveillance in hepatitis C virus-positive cirrhotic patients," Cancer Epidemiol Biomarkers Prev, vol. 18, pp. 2929-32, Nov 2009.
[18] Y. B. Deng, et al., "Identification of genes preferentially methylated in hepatitis C virus-related hepatocellular carcinoma," Cancer Sci, vol. 101, pp. 1501-10, Jun 2010.
[19] B. K. Yoo, et al., "Transcription factor Late SV40 Factor (LSF) functions as an oncogene in hepatocellular carcinoma," Proc Natl Acad Sci U S A, vol. 107, pp. 8357-62, May 4 2010.
[20] M. N. McCall, et al., "Assessing affymetrix GeneChip microarray quality," BMC Bioinformatics, vol. 12, p. 137, 2011.
[21] J. Harbig, et al., "A sequence-based identification of the genes detected by probesets on the Affymetrix U133 plus 2.0 array," Nucleic Acids Res, vol. 33, p. e31, 2005.
[22] D. Abdueva, et al., "Experimental comparison and evaluation of the Affymetrix exon and U133Plus2 GeneChip arrays," PLoS One, vol. 2, p. e913, 2007.
[23] E. Wingender, et al., "TRANSFAC: a database on transcription factors and their DNA binding sites," Nucleic Acids Res, vol. 24, pp. 238-41, Jan 1 1996.
[24] M. J. Okoniewski and C. J. Miller, "Comprehensive analysis of affymetrix exon arrays using BioConductor," PLoS Comput Biol, vol. 4, p. e6, Feb 2008.
[25] C. Harbron, et al., "RefPlus: an R package extending the RMA Algorithm," Bioinformatics, vol. 23, pp. 2493-4, Sep 15 2007.
[26] L. Gautier, et al., "affy--analysis of Affymetrix GeneChip data at the probe level," Bioinformatics, vol. 20, pp. 307-15, Feb 12 2004.
[27] E. B. Wilson and J. Worcester, "Note on the t-Test," Proc Natl Acad Sci U S A, vol. 28, pp. 297-301, Jul 1942.
[28] L. Vertesi, "Power of the P value," Ann Emerg Med, vol. 16, pp. 375-6, Mar 1987.
[29] I. Y. Park, et al., "Aberrant epigenetic modifications in hepatocarcinogenesis induced by hepatitis B virus X protein," Gastroenterology, vol. 132, pp. 1476-94, Apr 2007.
[30] H. Takagi, et al., "Frequent epigenetic inactivation of SFRP genes in hepatocellular carcinoma," J Gastroenterol, vol. 43, pp. 378-89, 2008.
[31] Y. L. Shih, et al., "SFRP1 suppressed hepatoma cells growth through Wnt
29
canonical signaling pathway," Int J Cancer, vol. 121, pp. 1028-35, Sep 1 2007.
[32] A. Hamosh, et al., "Online Mendelian Inheritance in Man (OMIM)," Hum Mutat, vol. 15, pp. 57-61, 2000.
[33] X. Cui and G. A. Churchill, "Statistical tests for differential expression in cDNA microarray experiments," Genome Biol, vol. 4, p. 210, 2003.
指導教授 洪炯宗(Jorng-Tzong Horng) 審核日期 2011-8-26
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