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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 阮雪芬 | - |
| dc.contributor.author | Chien-Wei Tseng | en |
| dc.contributor.author | 曾建偉 | zh_TW |
| dc.date.accessioned | 2021-05-20T21:01:17Z | - |
| dc.date.available | 2014-07-27 | - |
| dc.date.available | 2021-05-20T21:01:17Z | - |
| dc.date.copyright | 2011-07-27 | - |
| dc.date.issued | 2011 | - |
| dc.date.submitted | 2011-07-20 | - |
| dc.identifier.citation | [1] Bartel, D. P., MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116, 281-297.
[2] Guo, H., Ingolia, N. T., Weissman, J. S., Bartel, D. P., Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 2010, 466, 835-840. [3] Doench, J. G., Sharp, P. A., Specificity of microRNA target selection in translational repression. Genes Dev 2004, 18, 504-511. [4] Esquela-Kerscher, A., Slack, F. J., Oncomirs - microRNAs with a role in cancer. Nat Rev Cancer 2006, 6, 259-269. [5] Asangani, I. A., Rasheed, S. A., Nikolova, D. A., Leupold, J. H., et al., MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation and metastasis in colorectal cancer. Oncogene 2008, 27, 2128-2136. [6] Meng, F., Henson, R., Wehbe-Janek, H., Ghoshal, K., et al., MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology 2007, 133, 647-658. [7] Lee, S. T., Chu, K., Oh, H. J., Im, W. S., et al., Let-7 microRNA inhibits the proliferation of human glioblastoma cells. J Neurooncol 2011, 102, 19-24. [8] Park, S. M., Shell, S., Radjabi, A. R., Schickel, R., et al., Let-7 prevents early cancer progression by suppressing expression of the embryonic gene HMGA2. Cell Cycle 2007, 6, 2585-2590. [9] Ohshima, K., Inoue, K., Fujiwara, A., Hatakeyama, K., et al., Let-7 microRNA family is selectively secreted into the extracellular environment via exosomes in a metastatic gastric cancer cell line. PLoS One 2010, 5, e13247. [10] Huang, J. C., Babak, T., Corson, T. W., Chua, G., et al., Using expression profiling data to identify human microRNA targets. Nat Methods 2007, 4, 1045-1049. [11] Li, J., Min, R., Bonner, A., Zhang, Z., A probabilistic framework to improve microrna target prediction by incorporating proteomics data. J Bioinform Comput Biol 2009, 7, 955-972. [12] Bartel, D. P., MicroRNAs: target recognition and regulatory functions. Cell 2009, 136, 215-233. [13] Baek, D., Villen, J., Shin, C., Camargo, F. D., et al., The impact of microRNAs on protein output. Nature 2008, 455, 64-71. [14] Selbach, M., Schwanhausser, B., Thierfelder, N., Fang, Z., et al., Widespread changes in protein synthesis induced by microRNAs. Nature 2008, 455, 58-63. [15] Yu, X., Lin, J., Zack, D. J., Mendell, J. T., Qian, J., Analysis of regulatory network topology reveals functionally distinct classes of microRNAs. Nucleic Acids Res 2008, 36, 6494-6503. [16] Liang, H., Li, W. H., MicroRNA regulation of human protein protein interaction network. RNA 2007, 13, 1402-1408. [17] Cusick, M. E., Klitgord, N., Vidal, M., Hill, D. E., Interactome: gateway into systems biology. Hum Mol Genet 2005, 14 Spec No. 2, R171-181. [18] Rual, J. F., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., et al., Towards a proteome-scale map of the human protein-protein interaction network. Nature 2005, 437, 1173-1178. [19] Sharan, R., Ulitsky, I., Shamir, R., Network-based prediction of protein function. Mol Syst Biol 2007, 3, 88. [20] Hsu, C. W., Juan, H. F., Huang, H. C., Characterization of microRNA-regulated protein-protein interaction network. Proteomics 2008, 8, 1975-1979. [21] Zhang, H., Li, Y., Lai, M., The microRNA network and tumor metastasis. Oncogene 2010, 29, 937-948. [22] Lee, Y., Yang, X., Huang, Y., Fan, H., et al., Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. PLoS Comput Biol 2010, 6, e1000730. [23] Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., et al., Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 2004, 3, 1154-1169. [24] Han, C. L., Chien, C. W., Chen, W. C., Chen, Y. R., et al., A multiplexed quantitative strategy for membrane proteomics: opportunities for mining therapeutic targets for autosomal dominant polycystic kidney disease. Mol Cell Proteomics 2008, 7, 1983-1997. [25] Yang, Y., Chaerkady, R., Beer, M. A., Mendell, J. T., Pandey, A., Identification of miR-21 targets in breast cancer cells using a quantitative proteomic approach. Proteomics 2009, 9, 1374-1384. [26] Takei, Y., Takigahira, M., Mihara, K., Tarumi, Y., Yanagihara, K., The metastasis-associated microRNA miR-516a-3p is a novel therapeutic target for inhibiting peritoneal dissemination of human scirrhous gastric cancer. Cancer Res 2011, 71, 1442-1453. [27] Lewis, B. P., Burge, C. B., Bartel, D. P., Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005, 120, 15-20. [28] Krek, A., Grun, D., Poy, M. N., Wolf, R., et al., Combinatorial microRNA target predictions. Nat Genet 2005, 37, 495-500. [29] Komiya, Y., Kurabe, N., Katagiri, K., Ogawa, M., et al., A novel binding factor of 14-3-3beta functions as a transcriptional repressor and promotes anchorage-independent growth, tumorigenicity, and metastasis. J Biol Chem 2008, 283, 18753-18764. [30] Chan, C. H., Ko, C. C., Chang, J. G., Chen, S. F., et al., Subcellular and functional proteomic analysis of the cellular responses induced by Helicobacter pylori. Mol Cell Proteomics 2006, 5, 702-713. [31] Morrison, D. K., The 14-3-3 proteins: integrators of diverse signaling cues that impact cell fate and cancer development. Trends Cell Biol 2009, 19, 16-23. [32] Qi, W., Liu, X., Qiao, D., Martinez, J. D., Isoform-specific expression of 14-3-3 proteins in human lung cancer tissues. Int J Cancer 2005, 113, 359-363. [33] Cochran, D. A., Evans, C. A., Blinco, D., Burthem, J., et al., Proteomic analysis of chronic lymphocytic leukemia subtypes with mutated or unmutated Ig V(H) genes. Mol Cell Proteomics 2003, 2, 1331-1341. [34] Takihara, Y., Matsuda, Y., Hara, J., Role of the beta isoform of 14-3-3 proteins in cellular proliferation and oncogenic transformation. Carcinogenesis 2000, 21, 2073-2077. [35] Han, D. C., Rodriguez, L. G., Guan, J. L., Identification of a novel interaction between integrin beta1 and 14-3-3beta. Oncogene 2001, 20, 346-357. [36] Jemal, A., Bray, F., Center, M. M., Ferlay, J., et al., Global cancer statistics. CA Cancer J Clin 2011, 61, 69-90. [37] Macdonald, J. S., Gastric cancer--new therapeutic options. N Engl J Med 2006, 355, 76-77. [38] Yamazaki, H., Oshima, A., Murakami, R., Endoh, S., Ubukata, T., A long-term follow-up study of patients with gastric cancer detected by mass screening. Cancer 1989, 63, 613-617. [39] Kodama, I., Koufuji, K., Kawabata, S., Tetsu, S., et al., The clinical efficacy of CA 72-4 as serum marker for gastric cancer in comparison with CA19-9 and CEA. Int Surg 1995, 80, 45-48. [40] Ohuchi, N., Takahashi, K., Matoba, N., Sato, T., et al., Comparison of serum assays for TAG-72, CA19-9 and CEA in gastrointestinal carcinoma patients. Jpn J Clin Oncol 1989, 19, 242-248. [41] Hao, Y., Yu, Y., Wang, L., Yan, M., et al., IPO-38 is identified as a novel serum biomarker of gastric cancer based on clinical proteomics technology. J Proteome Res 2008, 7, 3668-3677. [42] Ychou, M., Duffour, J., Kramar, A., Gourgou, S., Grenier, J., Clinical significance and prognostic value of CA72-4 compared with CEA and CA19-9 in patients with gastric cancer. Dis Markers 2000, 16, 105-110. [43] D'Errico, M., de Rinaldis, E., Blasi, M. F., Viti, V., et al., Genome-wide expression profile of sporadic gastric cancers with microsatellite instability. Eur J Cancer 2009, 45, 461-469. [44] Tusher, V. G., Tibshirani, R., Chu, G., Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001, 98, 5116-5121. [45] Saeed, A. I., Bhagabati, N. K., Braisted, J. C., Liang, W., et al., TM4 microarray software suite. Methods Enzymol 2006, 411, 134-193. [46] Friedman, R. C., Farh, K. K., Burge, C. B., Bartel, D. P., Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 2009, 19, 92-105. [47] Keshava Prasad, T. S., Goel, R., Kandasamy, K., Keerthikumar, S., et al., Human Protein Reference Database--2009 update. Nucleic Acids Res 2009, 37, D767-772. [48] Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., et al., Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000, 25, 25-29. [49] Maere, S., Heymans, K., Kuiper, M., BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 2005, 21, 3448-3449. [50] Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., et al., Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13, 2498-2504. [51] Chang, C. C., Shih, J. Y., Jeng, Y. M., Su, J. L., et al., Connective tissue growth factor and its role in lung adenocarcinoma invasion and metastasis. J Natl Cancer Inst 2004, 96, 364-375. [52] Papagiannakopoulos, T., Shapiro, A., Kosik, K. S., MicroRNA-21 targets a network of key tumor-suppressive pathways in glioblastoma cells. Cancer Res 2008, 68, 8164-8172. [53] Lauren, P., The Two Histological Main Types of Gastric Carcinoma: Diffuse and So-Called Intestinal-Type Carcinoma. An Attempt at a Histo-Clinical Classification. Acta Pathol Microbiol Scand 1965, 64, 31-49. [54] Sobin LH, W. C., eds., TNM classification of malignant tumors. 1997, 5th ed. [55] Xiao, T., Ying, W., Li, L., Hu, Z., et al., An approach to studying lung cancer-related proteins in human blood. Mol Cell Proteomics 2005, 4, 1480-1486. [56] Chen, G., Gharib, T. G., Wang, H., Huang, C. C., et al., Protein profiles associated with survival in lung adenocarcinoma. Proc Natl Acad Sci U S A 2003, 100, 13537-13542. [57] Katayama, M., Sanzen, N., Funakoshi, A., Sekiguchi, K., Laminin gamma2-chain fragment in the circulation: a prognostic indicator of epithelial tumor invasion. Cancer Res 2003, 63, 222-229. [58] Juan, H. F., Wang, I. H., Huang, T. C., Li, J. J., et al., Proteomics analysis of a novel compound: cyclic RGD in breast carcinoma cell line MCF-7. Proteomics 2006, 6, 2991-3000. [59] Lin, L. L., Chen, C. N., Lin, W. C., Lee, P. H., et al., Annexin A4: A novel molecular marker for gastric cancer with Helicobacter pylori infection using proteomics approach. Proteomics Clin Appl 2008, 2, 619-634. [60] Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., et al., Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 2005, 433, 769-773. [61] Bajou, K., Noel, A., Gerard, R. D., Masson, V., et al., Absence of host plasminogen activator inhibitor 1 prevents cancer invasion and vascularization. Nat Med 1998, 4, 923-928. [62] Liu, G., Shuman, M. A., Cohen, R. L., Co-expression of urokinase, urokinase receptor and PAI-1 is necessary for optimum invasiveness of cultured lung cancer cells. Int J Cancer 1995, 60, 501-506. [63] Chambers, S. K., Ivins, C. M., Carcangiu, M. L., Plasminogen activator inhibitor-1 is an independent poor prognostic factor for survival in advanced stage epithelial ovarian cancer patients. Int J Cancer 1998, 79, 449-454. [64] Lai, S. Y., Ziober, A. F., Lee, M. N., Cohen, N. A., et al., Activated Vav2 modulates cellular invasion through Rac1 and Cdc42 in oral squamous cell carcinoma. Oral Oncol 2008, 44, 683-688. [65] Bourguignon, L. Y., Zhu, H., Zhou, B., Diedrich, F., et al., Hyaluronan promotes CD44v3-Vav2 interaction with Grb2-p185(HER2) and induces Rac1 and Ras signaling during ovarian tumor cell migration and growth. J Biol Chem 2001, 276, 48679-48692. [66] Koike, T., Kimura, N., Miyazaki, K., Yabuta, T., et al., Hypoxia induces adhesion molecules on cancer cells: A missing link between Warburg effect and induction of selectin-ligand carbohydrates. Proc Natl Acad Sci U S A 2004, 101, 8132-8137. [67] Landemaine, T., Jackson, A., Bellahcene, A., Rucci, N., et al., A six-gene signature predicting breast cancer lung metastasis. Cancer Res 2008, 68, 6092-6099. [68] Sultmann, H., von Heydebreck, A., Huber, W., Kuner, R., et al., Gene expression in kidney cancer is associated with cytogenetic abnormalities, metastasis formation, and patient survival. Clin Cancer Res 2005, 11, 646-655. [69] Chen, J., De, S., Brainard, J., Byzova, T. V., Metastatic properties of prostate cancer cells are controlled by VEGF. Cell Commun Adhes 2004, 11, 1-11. [70] Patel, V., Rosenfeldt, H. M., Lyons, R., Servitja, J. M., et al., Persistent activation of Rac1 in squamous carcinomas of the head and neck: evidence for an EGFR/Vav2 signaling axis involved in cell invasion. Carcinogenesis 2007, 28, 1145-1152. [71] Lujambio, A., Calin, G. A., Villanueva, A., Ropero, S., et al., A microRNA DNA methylation signature for human cancer metastasis. Proc Natl Acad Sci U S A 2008, 105, 13556-13561. [72] Giraldez, A. J., Cinalli, R. M., Glasner, M. E., Enright, A. J., et al., MicroRNAs regulate brain morphogenesis in zebrafish. Science 2005, 308, 833-838. [73] Christensen, M., Schratt, G. M., microRNA involvement in developmental and functional aspects of the nervous system and in neurological diseases. Neurosci Lett 2009, 466, 55-62. [74] Friedlander, R. M., Apoptosis and caspases in neurodegenerative diseases. N Engl J Med 2003, 348, 1365-1375. [75] Yuan, J., Yankner, B. A., Apoptosis in the nervous system. Nature 2000, 407, 802-809. [76] Gervais, F. G., Xu, D., Robertson, G. S., Vaillancourt, J. P., et al., Involvement of caspases in proteolytic cleavage of Alzheimer's amyloid-beta precursor protein and amyloidogenic A beta peptide formation. Cell 1999, 97, 395-406. [77] Garden, G. A., Budd, S. L., Tsai, E., Hanson, L., et al., Caspase cascades in human immunodeficiency virus-associated neurodegeneration. J Neurosci 2002, 22, 4015-4024. [78] Klepper, J., Wang, D., Fischbarg, J., Vera, J. C., et al., Defective glucose transport across brain tissue barriers: a newly recognized neurological syndrome. Neurochem Res 1999, 24, 587-594. [79] Mooradian, A. D., Chung, H. C., Shah, G. N., GLUT-1 expression in the cerebra of patients with Alzheimer's disease. Neurobiol Aging 1997, 18, 469-474. [80] Simpson, I. A., Chundu, K. R., Davies-Hill, T., Honer, W. G., Davies, P., Decreased concentrations of GLUT1 and GLUT3 glucose transporters in the brains of patients with Alzheimer's disease. Ann Neurol 1994, 35, 546-551. [81] Xia, H. H., Yang, Y., Chu, K. M., Gu, Q., et al., Serum macrophage migration-inhibitory factor as a diagnostic and prognostic biomarker for gastric cancer. Cancer 2009, 115, 5441-5449. [82] Lim, J. W., Kim, H., Kim, J. M., Kim, J. S., et al., Cellular stress-related protein expression in Helicobacter pylori-infected gastric epithelial AGS cells. Int J Biochem Cell Biol 2004, 36, 1624-1634. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10091 | - |
| dc.description.abstract | 胃癌在全世界中為癌症致死率的第二名(世界衛生組織2009年報導)。
被診斷晚末期的胃癌病人五年存活率不到35%。較差的預後能力主要與腫瘤轉移有關。此外,有些微型核醣核酸被報導與腫瘤相關,其功能可能是致癌基因或腫瘤抑制基因,並且涉及了腫瘤形成及癌症發展。在本研究中,我們研究胃癌轉移的機制並鑑定出一個抗轉移的微型核醣核酸-148a,它在腫瘤組織中的表現較低。Kaplan–Meier存活方法顯示,相較於含有較低微型核醣核酸-148a含量的病人(32.1%),其含有較高微型核醣核酸-148a含量的病人具有較高的五年整體存活率 (71.4%) (P = 0.03)。臨床資料指出微型核醣核酸-148a表現量增加與腫瘤遠處轉移(P = 0.043)、器官侵犯 (P = 0.013) 及腹膜侵犯 (P = 0.04) 有高度相關性。大量表現微型核醣核酸-148a減少腫瘤細胞侵犯、轉移及附著能力。此外,大量表現微型核醣核酸-148a抑制細胞生長並誘導細胞凋亡。我們利用了同位素標記相對和絕對定量方法分析微型核醣核酸-148a所調控的蛋白質體表現。微型核醣核酸-148a所調控的蛋白質體與腫瘤發展有高度相關性,其包括了細胞移動、生長與增生以及細胞凋亡。這些結果與我們之前的結果一致,微型核醣核酸-148a抑制胃癌細胞轉移相關的功能。另一方面,進一步的利用了冷光酶分析方法,我們確認了微型核醣核酸-148a可以直接調控14-3-3β表現。14-3-3β在腫瘤組織中的表現增加 (N = 40, P < 0.01),而且血液14-3-3β在胃癌病人的含量也顯著的比正常人高(N = 63) (P < 0.0001)。具有較高血液14-3-3β含量的病人有較差的整體存活率(P = 0.038)。大量表現14-3-3β增加了腫瘤細胞生長、侵犯與移動能力。綜合上述結果,14-3-3β涉及了胃癌的轉移。微型核醣核酸-148a也許功能上是個腫瘤抑制基因,並且透過調控一個有潛力作為胃癌偵測與預後的14-3-3β生物標記表現以抑制了腫瘤細胞的轉移。 | zh_TW |
| dc.description.abstract | Gastric cancer is the second leading cause of cancer deaths worldwide (WHO 2009 report). Patients diagnosed with advanced stages have a survival rate of less than 35% beyond 5 years. The poor prognosis is mainly related to tumor metastasis. In addition, some microRNAs (miRNAs) are reported as oncomirs which function as either oncogenes or tumor suppressors and involved in tumorigenesis and cancer progression. Here, we studied the mechanisms of gastric cancer metastasis and identified an antimetastatic miRNA, miR-148a, that was down-regulated in tumor tissues. Kaplan–Meier survival method revealed that patients with higher miR-148a expression levels had higher 5-year overall survival rates (71.4%) compared with patients with low miR-148a levels (32.1%, P = 0.03). Clinical data indicated that elevated miR-148a levels highly correlated with distant metastasis (P = 0.043), organ (P = 0.013) and peritoneal invasion (P = 0.04). Over-expression of miR-148a could decrease invasiveness, migration and adhesion of tumor cells. Moreover, Over-expression of miR-148a could repress cell growth and induce cell apoptosis. We further used isobaric tag for relative and absolute quantitation (iTRAQ) method to analyze miR-148a-regulated proteome. The results showed that miR-148a-regulated proteome was closely related with tumor progression, including cell movement, growth and proliferation as well as cell death. These results are consistent with our previous data that miR-148a suppresses metastasis-related functions of gastric cancer cells. On the other hand, we verified that miR-148a could directly regulate 14-3-3β expression using luciferase assay. 14-3-3β levels were elevated in tumor tissues (N = 40, P < 0.01), and serum 14-3-3β levels in cancer patients (N = 145) were also significantly higher than healthy controls (N = 63) (P < 0.0001). Patients with higher serum 14-3-3β levels had worse overall survival (P = 0.038). Over-expression of 14-3-3β enhanced the growth, invasiveness and migration of tumor cells. In conclusion, 14-3-3β is involved in metastasis of gastric cancer. miR-148a may function as a tumor suppressor in gastric cancer, suppressing cell metastasis through targeting 14-3-3β, a potential detective and prognostic marker in gastric cancer. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T21:01:17Z (GMT). No. of bitstreams: 1
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| dc.description.tableofcontents | 口試委員會審定書 I
Acknowledgments II 中文摘要 IV ABSTRACT V CONTENTS VII LIST OF FINGURES X LIST OF TABLES XII Chapter 1 Introduction 1 1.1 Biogenesis of miRNAs and Their Roles in Cancers 1 1.2 Analysis of Correlation Between miRNAs and Target Genes 1 1.3 miRNA-regulated Network and Biological Functions 2 1.4 miRNA-regulated Proteome and Associated Biological Functions 3 1.5 14-3-3β 4 1.5.1 Role of 14-3-3β in Cancers 4 1.5.2 Biomarkers for Gastric Cancer 5 1.6 Motivation 6 Chapter 2 Materials and Methods 7 2.1 Expression Profiles of miRNAs and mRNA 7 2.2 Tissue Specimens 8 2.3 MiRNA-regulated PIN Identification and Analysis 9 2.4 qRT-PCR for miRNA 10 2.5 Cell Culture and Authentication of Cell Lines 10 2.6 Cell Invasion and Migration Assays Using Boyden Chambers 10 2.7 Wound Healing Assay 11 2.8 Cell Adhesion Assay 11 2. 9 Cell Proliferation Assay 12 2.10 Luciferase Reporter Assay 12 2.11 Protein Extraction 13 2.12 Immunoblotting 14 2.13 Isobaric Tag for Relative and Absolute Quantitation (iTRAQ) 14 2.13.1 Gel-Assisted Digestion of Cell Lysate 15 2.13.2 iTRAQ Labeling and Fractionation by Strong Cation Exchange (SCX) Chromatograph 15 2.13.3 LC-MS/MS Analysis 16 2.13.4 Data Processing and Analysis 17 2.14 Ingenuity Pathway Analysis (IPA) 18 2.15 Gastric Cancer Patients and Clinical Data 19 2.16 Blood and Tissue Sample Collection 20 2.17 ELISA for 14-3-3β 20 2.18 Construction of the 14-3-3β Over-expressing Plasmid 21 2.19 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) Assay for Cell Growth 21 2.20 Two Dimensional Electrophoresis and Image Analysis 21 2.21 In-gel Digestion and Mass Spectrometry 22 2.22 Statistical Analysis 24 Chapter 3 Results 26 3.1 MicroRNA-regulated PINs in Gastric Cancer 26 3.2 The Potential Functions of Oncomir-regulated PINs 28 3.3 MiR-148a-regulated PIN and Its Potential Functions in Gastric Cancer 28 3.4 PAI-1, ITGB8, VAV2 and ITGA5 Are Oncogenes and Direct Targets of MiR-148a 29 3.5 The Correlation Between miR-148a and Clinicopathological Factors 31 3.6 MiR-148a Inhibits Cell Invasion, Migration, Adhesion and Growth 31 3.7 miR-148a Induces Apoptosis of Gastric Cancer Cells 32 3.8 miR-148a-regulated Proteome and Associated Biological Functions 32 3.9 14-3-3β Is a Direct Target of miR-148a 34 3.10 14-3-3β Expression Is Positively Correlated with Aggressive Phenotypes of Gastric Cancer Cells 35 3.11 Over-expression of 14-3-3β Enhances Cancer Cell Invasion, Migration and Growth 37 3.12 14-3-3β Expression in Tumor Tissues and Serum from Gastric Cancer Patients 37 3.13 Serum 14-3-3β Levels and Overall and Recurrence-free Survival 38 3.14 Serum 14-3-3β Levels Decrease after Gastrectomy with D2 Lymphadenectomy 39 3.15 ROC Curves of 14-3-3β in Gastric Cancer 39 3.16 The Relationship Between 14-3-3β Expression Level and Metastatic Lymph Node Number, Tumor Size and Cancer Stage 40 Chapter 4 Discussion 41 Chapter 5 Conclusion 46 Chapter 6 References 48 Appendix 95 | - |
| dc.language.iso | en | - |
| dc.title | MicroRNA-148a與其標靶基因14-3-3β在胃癌轉移機制之探討 | zh_TW |
| dc.title | The Metastatic Mechanism of MicroRNA-148a and Its Target Gene 14-3-3β in Gastric Cancer | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 99-2 | - |
| dc.description.degree | 博士 | - |
| dc.contributor.oralexamcommittee | 陳炯年,黃宣誠,李岳倫,陳倩瑜 | - |
| dc.subject.keyword | 微型核醣核酸-148a,14-3-3β,胃癌,轉移,生物標記, | zh_TW |
| dc.subject.keyword | miR-148a,14-3-3β,gastric cancer,metastasis,biomarker, | en |
| dc.relation.page | 136 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2011-07-20 | - |
| dc.contributor.author-college | 生命科學院 | zh_TW |
| dc.contributor.author-dept | 分子與細胞生物學研究所 | zh_TW |
| 顯示於系所單位: | 分子與細胞生物學研究所 | |
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