請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77287完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林亮音(Liang-In Lin) | |
| dc.contributor.author | Yu-Hsuan Fu | en |
| dc.contributor.author | 傅宇暄 | zh_TW |
| dc.date.accessioned | 2021-07-10T21:54:17Z | - |
| dc.date.available | 2021-07-10T21:54:17Z | - |
| dc.date.copyright | 2019-08-28 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-09 | |
| dc.identifier.citation | 1. Short, N.J., M.E. Rytting, and J.E. Cortes, Acute myeloid leukaemia. Lancet, 2018. 392(10147): p. 593-606.
2. Tenen, D.G., Disruption of differentiation in human cancer: AML shows the way. Nat Rev Cancer, 2003. 3(2): p. 89-101. 3. De Kouchkovsky, I. and M. Abdul-Hay, Acute myeloid leukemia: a comprehensive review and 2016 update. Blood Cancer Journal, 2016. 6: p. e441. 4. Vardiman, J.W., N.L. Harris, and R.D. Brunning, The World Health Organization (WHO) classification of the myeloid neoplasms. Blood, 2002. 100(7): p. 2292-302. 5. Vardiman, J.W., et al., The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood, 2009. 114(5): p. 937-51. 6. Arber, D.A., et al., The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood, 2016. 127(20): p. 2391-405. 7. Saultz, J. and R. Garzon, Acute Myeloid Leukemia: A Concise Review. Journal of Clinical Medicine, 2016. 5(3): p. 33. 8. Dombret, H. and C. Gardin, An update of current treatments for adult acute myeloid leukemia. Blood, 2016. 127(1): p. 53. 9. Talati, C. and J.E. Lancet, CPX-351: changing the landscape of treatment for patients with secondary acute myeloid leukemia. Future Oncol, 2018. 14(12): p. 1147-1154. 10. Stone, R.M., et al., Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation. N Engl J Med, 2017. 377(5): p. 454-464. 11. Levis, M., Midostaurin approved for FLT3-mutated AML. Blood, 2017. 12. Dhillon, S., Gilteritinib: First Global Approval. Drugs, 2019. 79(3): p. 331-339. 13. Wei, A.H. and I.S. Tiong, Midostaurin, enasidenib, CPX-351, gemtuzumab ozogamicin, and venetoclax bring new hope to AML. Blood, 2017. 130(23): p. 2469-2474. 14. Liu, Y., et al., Immunotherapy in acute myeloid leukemia and myelodysplastic syndromes: The dawn of a new era? Blood Rev, 2019. 34: p. 67-83. 15. Meshinchi, S. and F.R. Appelbaum, Structural and functional Alterations of FLT3 in Acute Myeloid Leukemia. Clinical cancer research : an official journal of the American Association for Cancer Research, 2009. 15(13): p. 4263-4269. 16. Stirewalt, D.L. and J.P. Radich, The role of FLT3 in haematopoietic malignancies. Nat Rev Cancer, 2003. 3(9): p. 650-665. 17. Wander, S.A., M.J. Levis, and A.T. Fathi, The evolving role of FLT3 inhibitors in acute myeloid leukemia: quizartinib and beyond. Therapeutic Advances in Hematology, 2014. 5(3): p. 65-77. 18. Larrosa-Garcia, M. and M.R. Baer, FLT3 Inhibitors in Acute Myeloid Leukemia: Current Status and Future Directions. Mol Cancer Ther, 2017. 16(6): p. 991-1001. 19. Choi, Y., et al., Novel mutations in the FLT3 gene in adult patients with refractory acute myeloid leukemia. Leukemia, 2004. 19(1): p. 141-143. 20. Liang, D.C., et al., FLT3-TKD mutation in childhood acute myeloid leukemia. Leukemia, 2003. 17(5): p. 883-886. 21. Bagrintseva, K., et al., Mutations in the tyrosine kinase domain of FLT3 define a new molecular mechanism of acquired drug resistance to PTK inhibitors in FLT3-ITD–transformed hematopoietic cells. Blood, 2004. 103(6): p. 2266-2275. 22. Cioccio, J. and D. Claxton, Therapy of acute myeloid leukemia: therapeutic targeting of tyrosine kinases. Expert Opin Investig Drugs, 2019. 28(4): p. 337-349. 23. Fathi, A.T., et al., A Phase I Study of the Multi-Targeted Tyrosine Kinase Inhibitor Cabozantinib in Patients with Acute Myeloid Leukemia. Blood, 2016. 128(22): p. 5218-5218. 24. Deeks, E.D., Cabozantinib: A Review in Advanced Hepatocellular Carcinoma. Target Oncol, 2019. 14(1): p. 107-113. 25. Lu, J.W., et al., Cabozantinib is selectively cytotoxic in acute myeloid leukemia cells with FLT3-internal tandem duplication (FLT3-ITD). Cancer Lett, 2016. 376(2): p. 218-25. 26. Klaeger, S., et al., The target landscape of clinical kinase drugs. Science, 2017. 358(6367): p. eaan4368. 27. Fathi, A.T., et al., Cabozantinib is well tolerated in acute myeloid leukemia and effectively inhibits the resistance-conferring FLT3/tyrosine kinase domain/F691 mutation. Cancer, 2018. 124(2): p. 306-314. 28. Lacy, S., et al., A population pharmacokinetic model of cabozantinib in healthy volunteers and patients with various cancer types. Cancer Chemother Pharmacol, 2018. 81(6): p. 1071-1082. 29. Nguyen, L., et al., Pharmacokinetics of cabozantinib tablet and capsule formulations in healthy adults. Anticancer Drugs, 2016. 27(7): p. 669-78. 30. Lan, P.-Q., Establishment, characterization and treatment strategy of cabozantinib-resistant Molm13-XR leukemic cells. Master thesis, National Taiwan University, 2017. 31. Chen, W.-C., Establishment, characterization and treatment strategy of cabozantinib-resistant MV4-11-XR leukemic cells. Master thesis, National Taiwan University, 2016. 32. Mootha, V.K., et al., PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet, 2003. 34(3): p. 267-73. 33. Subramanian, A., et al., Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A, 2005. 102(43): p. 15545-50. 34. Pang, Z., et al., High PKD2 predicts poor prognosis in lung adenocarcinoma via promoting Epithelial-mesenchymal Transition. Sci Rep, 2019. 9(1): p. 1324. 35. Huang, R., X. Liao, and Q. Li, Identification of key pathways and genes in TP53 mutation acute myeloid leukemia: evidence from bioinformatics analysis. Onco Targets Ther, 2018. 11: p. 163-173. 36. Kakiuchi, S., et al., NANOG Expression as a Responsive Biomarker during Treatment with Hedgehog Signal Inhibitor in Acute Myeloid Leukemia. Int J Mol Sci, 2017. 18(3). 37. Lamb, J., et al., The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science, 2006. 313(5795): p. 1929-35. 38. Lamb, J., The Connectivity Map: a new tool for biomedical research. Nat Rev Cancer, 2007. 7(1): p. 54-60. 39. Wen, Z., et al., Discovery of molecular mechanisms of traditional Chinese medicinal formula Si-Wu-Tang using gene expression microarray and connectivity map. PLoS One, 2011. 6(3): p. e18278. 40. Lee, K.H., et al., A gene expression signature-based approach reveals the mechanisms of action of the Chinese herbal medicine berberine. Sci Rep, 2014. 4: p. 6394. 41. Kim, B.Y., J. Lee, and N.S. Kim, Helveticoside is a biologically active component of the seed extract of Descurainia sophia and induces reciprocal gene regulation in A549 human lung cancer cells. BMC Genomics, 2015. 16: p. 713. 42. Hieronymus, H., et al., Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators. Cancer Cell, 2006. 10(4): p. 321-30. 43. Lv, J., et al., Detection and screening of small molecule agents for overcoming Sorafenib resistance of hepatocellular carcinoma: a bioinformatics study. Int J Clin Exp Med, 2015. 8(2): p. 2317-25. 44. Wei, G., et al., Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance. Cancer Cell, 2006. 10(4): p. 331-42. 45. Subramanian, A., et al., A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell, 2017. 171(6): p. 1437-1452 e17. 46. Warburg, O., F. Wind, and E. Negelein, THE METABOLISM OF TUMORS IN THE BODY. J Gen Physiol, 1927. 8(6): p. 519-30. 47. Warburg, O., The Metabolism of Carcinoma Cells. The Journal of Cancer Research, 1925. 9(1): p. 148-163. 48. Warburg, O., On the origin of cancer cells. Science, 1956. 123(3191): p. 309-14. 49. Racker, E., Bioenergetics and the problem of tumor growth. Am Sci, 1972. 60(1): p. 56-63. 50. Flier, J.S., et al., Elevated levels of glucose transport and transporter messenger RNA are induced by ras or src oncogenes. Science, 1987. 235(4795): p. 1492-5. 51. Vander Heiden, M.G., L.C. Cantley, and C.B. Thompson, Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science, 2009. 324(5930): p. 1029-33. 52. Liberti, M.V. and J.W. Locasale, The Warburg Effect: How Does it Benefit Cancer Cells? Trends Biochem Sci, 2016. 41(3): p. 211-218. 53. Locasale, J.W. and L.C. Cantley, Metabolic flux and the regulation of mammalian cell growth. Cell Metab, 2011. 14(4): p. 443-51. 54. Patra, K.C. and N. Hay, The pentose phosphate pathway and cancer. Trends Biochem Sci, 2014. 39(8): p. 347-54. 55. De Preter, G., et al., Inhibition of the pentose phosphate pathway by dichloroacetate unravels a missing link between aerobic glycolysis and cancer cell proliferation. Oncotarget, 2016. 7(3): p. 2910-20. 56. Duvel, K., et al., Activation of a metabolic gene regulatory network downstream of mTOR complex 1. Mol Cell, 2010. 39(2): p. 171-83. 57. Weiss, R.B. and B.F. Issell, The nitrosoureas: carmustine (BCNU) and lomustine (CCNU). Cancer Treat Rev, 1982. 9(4): p. 313-30. 58. Pigneux, A., et al., Improved Survival by Adding Lomustine to Conventional Chemotherapy for Elderly Patients With AML Without Unfavorable Cytogenetics: Results of the LAM-SA 2007 FILO Trial. Journal of Clinical Oncology, 2018. 36(32): p. 3203-3210. 59. Pigneux, A., et al., Addition of lomustine to idarubicin and cytarabine improves the outcome of elderly patients with de novo acute myeloid leukemia: a report from the GOELAMS. J Clin Oncol, 2010. 28(18): p. 3028-34. 60. Yufu, Y., J. Nishimura, and H. Nawata, High constitutive expression of heat shock protein 90 alpha in human acute leukemia cells. Leuk Res, 1992. 16(6-7): p. 597-605. 61. Yao, Q., et al., FLT3 expressing leukemias are selectively sensitive to inhibitors of the molecular chaperone heat shock protein 90 through destabilization of signal transduction-associated kinases. Clin Cancer Res, 2003. 9(12): p. 4483-93. 62. Minami, Y., et al., Selective apoptosis of tandemly duplicated FLT3-transformed leukemia cells by Hsp90 inhibitors. Leukemia, 2002. 16(8): p. 1535-40. 63. Lazenby, M., et al., The HSP90 inhibitor ganetespib: A potential effective agent for Acute Myeloid Leukemia in combination with cytarabine. Leuk Res, 2015. 39(6): p. 617-24. 64. Lu, X., et al., Hsp90 inhibitors and drug resistance in cancer: the potential benefits of combination therapies of Hsp90 inhibitors and other anti-cancer drugs. Biochem Pharmacol, 2012. 83(8): p. 995-1004. 65. Walsby, E.J., et al., The HSP90 inhibitor NVP-AUY922-AG inhibits the PI3K and IKK signalling pathways and synergizes with cytarabine in acute myeloid leukaemia cells. Br J Haematol, 2013. 161(1): p. 57-67. 66. Yu, C., R.K. Kancha, and J. Duyster, Targeting oncoprotein stability overcomes drug resistance caused by FLT3 kinase domain mutations. PLoS One, 2014. 9(5): p. e97116. 67. Katayama, K., K. Noguchi, and Y. Sugimoto, Heat shock protein 90 inhibitors overcome the resistance to Fms-like tyrosine kinase 3 inhibitors in acute myeloid leukemia. Oncotarget, 2018. 9(76): p. 34240-34258. 68. Ersahin, T., N. Tuncbag, and R. Cetin-Atalay, The PI3K/AKT/mTOR interactive pathway. Mol Biosyst, 2015. 11(7): p. 1946-54. 69. Courtnay, R., et al., Cancer metabolism and the Warburg effect: the role of HIF-1 and PI3K. Mol Biol Rep, 2015. 42(4): p. 841-51. 70. Tamburini, J., et al., Constitutive phosphoinositide 3-kinase/Akt activation represents a favorable prognostic factor in de novo acute myelogenous leukemia patients. Blood, 2007. 110(3): p. 1025-8. 71. Xu, Q., et al., Survival of acute myeloid leukemia cells requires PI3 kinase activation. Blood, 2003. 102(3): p. 972-80. 72. Bertacchini, J., et al., Targeting PI3K/AKT/mTOR network for treatment of leukemia. Cell Mol Life Sci, 2015. 72(12): p. 2337-47. 73. Recher, C., et al., Antileukemic activity of rapamycin in acute myeloid leukemia. Blood, 2005. 105(6): p. 2527-34. 74. Martelli, A.M., et al., Two hits are better than one: targeting both phosphatidylinositol 3-kinase and mammalian target of rapamycin as a therapeutic strategy for acute leukemia treatment. Oncotarget, 2012. 3(4): p. 371-94. 75. Herschbein, L. and J.L. Liesveld, Dueling for dual inhibition: Means to enhance effectiveness of PI3K/Akt/mTOR inhibitors in AML. Blood Rev, 2018. 32(3): p. 235-248. 76. Mallon, R., et al., Antitumor efficacy of PKI-587, a highly potent dual PI3K/mTOR kinase inhibitor. Clin Cancer Res, 2011. 17(10): p. 3193-203. 77. D'Amato, V., et al., The dual PI3K/mTOR inhibitor PKI-587 enhances sensitivity to cetuximab in EGFR-resistant human head and neck cancer models. Br J Cancer, 2014. 110(12): p. 2887-95. 78. Lindblad, O., et al., Aberrant activation of the PI3K/mTOR pathway promotes resistance to sorafenib in AML. Oncogene, 2016. 35(39): p. 5119-31. 79. Knight, S.D., et al., Discovery of GSK2126458, a Highly Potent Inhibitor of PI3K and the Mammalian Target of Rapamycin. ACS Med Chem Lett, 2010. 1(1): p. 39-43. 80. Kari, G., U. Rodeck, and A.P. Dicker, Zebrafish: an emerging model system for human disease and drug discovery. Clin Pharmacol Ther, 2007. 82(1): p. 70-80. 81. Ridges, S., et al., Zebrafish screen identifies novel compound with selective toxicity against leukemia. Blood, 2012. 119(24): p. 5621-31. 82. Deveau, A.P., V.L. Bentley, and J.N. Berman, Using zebrafish models of leukemia to streamline drug screening and discovery. Exp Hematol, 2017. 45: p. 1-9. 83. Lu, J.W., et al., Zebrafish as a Model for the Study of Human Myeloid Malignancies. Biomed Res Int, 2015. 2015: p. 641475. 84. Langmead, B. and S.L. Salzberg, Fast gapped-read alignment with Bowtie 2. Nat Methods, 2012. 9(4): p. 357-9. 85. Li, B. and C.N. Dewey, RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics, 2011. 12: p. 323. 86. Leng, N., et al., EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics, 2013. 29(8): p. 1035-43. 87. Poplin, R., et al., Scaling accurate genetic variant discovery to tens of thousands of samples. bioRxiv, 2018: p. 201178. 88. Wang, K., M. Li, and H. Hakonarson, ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res, 2010. 38(16): p. e164. 89. Nicorici, D., et al., FusionCatcher - a tool for finding somatic fusion genes in paired-end RNA-sequencing data. bioRxiv, 2014: p. 011650. 90. Huang, D.W., et al., The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol, 2007. 8(9): p. R183. 91. Kanehisa, M. and S. Goto, KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res, 2000. 28(1): p. 27-30. 92. Cunningham, F., et al., Ensembl 2019. Nucleic Acids Res, 2018. 93. Freed-Pastor, W.A. and C. Prives, Mutant p53: one name, many proteins. Genes Dev, 2012. 26(12): p. 1268-86. 94. Ley, T.J., et al., Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med, 2013. 368(22): p. 2059-74. 95. Ohgami, R.S., et al., Next-generation sequencing of acute myeloid leukemia identifies the significance of TP53, U2AF1, ASXL1, and TET2 mutations. Mod Pathol, 2015. 28(5): p. 706-14. 96. Tefferi, A., Novel mutations and their functional and clinical relevance in myeloproliferative neoplasms: JAK2, MPL, TET2, ASXL1, CBL, IDH and IKZF1. Leukemia, 2010. 24(6): p. 1128-38. 97. Wang, Y., et al., Recurrent Fusion Genes in Leukemia: An Attractive Target for Diagnosis and Treatment. Curr Genomics, 2017. 18(5): p. 378-384. 98. Martinez-Soria, N., et al., The Oncogenic Transcription Factor RUNX1/ETO Corrupts Cell Cycle Regulation to Drive Leukemic Transformation. Cancer Cell, 2018. 34(4): p. 626-642.e8. 99. Schram, A.M., et al., Fusions in solid tumours: diagnostic strategies, targeted therapy, and acquired resistance. Nat Rev Clin Oncol, 2017. 14(12): p. 735-748. 100. Kulkarni, A., et al., BRAF Fusion as a Novel Mechanism of Acquired Resistance to Vemurafenib in BRAF(V600E) Mutant Melanoma. Clin Cancer Res, 2017. 23(18): p. 5631-5638. 101. Daly, C., et al., FGFR3-TACC3 fusion proteins act as naturally occurring drivers of tumor resistance by functionally substituting for EGFR/ERK signaling. Oncogene, 2017. 36(4): p. 471-481. 102. Drexler, H.G., H. Quentmeier, and R.A. MacLeod, Malignant hematopoietic cell lines: in vitro models for the study of MLL gene alterations. Leukemia, 2004. 18(2): p. 227-32. 103. Matsuo, Y., et al., Two acute monocytic leukemia (AML-M5a) cell lines (MOLM-13 and MOLM-14) with interclonal phenotypic heterogeneity showing MLL-AF9 fusion resulting from an occult chromosome insertion, ins(11;9)(q23;p22p23). Leukemia, 1997. 11(9): p. 1469-77. 104. Palau, A., et al., Immunophenotypic, cytogenetic, and mutational characterization of cell lines derived from myelodysplastic syndrome patients after progression to acute myeloid leukemia. Genes Chromosomes Cancer, 2017. 56(3): p. 243-252. 105. Jie-Wen Wu, N.K.M., Metabolic Alternations of Drug-Resistance Acute Myeloid Leukemia Harboring FLT3-ITD Mutation. Master thesis, National Taiwan University, 2018. 106. Zhang, C.C. and H.A. Sadek, Hypoxia and metabolic properties of hematopoietic stem cells. Antioxid Redox Signal, 2014. 20(12): p. 1891-901. 107. Palladino, M.A., et al., Myeloid cell leukemia-1 (Mc1-1) is a candidate target gene of hypoxia-inducible factor-1 (HIF-1) in the testis. Reprod Biol Endocrinol, 2012. 10: p. 104. 108. Dang, C.V., MYC, metabolism, cell growth, and tumorigenesis. Cold Spring Harb Perspect Med, 2013. 3(8). 109. Brondfield, S., et al., Direct and indirect targeting of MYC to treat acute myeloid leukemia. Cancer Chemother Pharmacol, 2015. 76(1): p. 35-46. 110. Peng, G. and Y. Liu, Hypoxia-inducible factors in cancer stem cells and inflammation. Trends Pharmacol Sci, 2015. 36(6): p. 374-83. 111. Mottet, D., et al., Regulation of hypoxia-inducible factor-1alpha protein level during hypoxic conditions by the phosphatidylinositol 3-kinase/Akt/glycogen synthase kinase 3beta pathway in HepG2 cells. J Biol Chem, 2003. 278(33): p. 31277-85. 112. Zhang, Q., et al., Hypoxia-induced HIF-1 alpha accumulation is augmented in a co-culture of keloid fibroblasts and human mast cells: involvement of ERK1/2 and PI-3K/Akt. Exp Cell Res, 2006. 312(2): p. 145-55. 113. Cho, J.H. and J.S. Han, Phospholipase D and Its Essential Role in Cancer. Mol Cells, 2017. 40(11): p. 805-813. 114. Choi, W.S., et al., Activation of RBL-2H3 mast cells is dependent on tyrosine phosphorylation of phospholipase D2 by Fyn and Fgr. Mol Cell Biol, 2004. 24(16): p. 6980-92. 115. Kang, D.W., K.Y. Choi, and D.S. Min, Functional regulation of phospholipase D expression in cancer and inflammation. J Biol Chem, 2014. 289(33): p. 22575-82. 116. Yin, H., et al., Dependence of phospholipase D1 multi-monoubiquitination on its enzymatic activity and palmitoylation. J Biol Chem, 2010. 285(18): p. 13580-8. 117. Yoshikawa, F., et al., Phospholipase D family member 4, a transmembrane glycoprotein with no phospholipase D activity, expression in spleen and early postnatal microglia. PLoS One, 2010. 5(11): p. e13932. 118. Mavrommati, I., et al., Novel roles for class II Phosphoinositide 3-Kinase C2beta in signalling pathways involved in prostate cancer cell invasion. Sci Rep, 2016. 6: p. 23277. 119. Liu, P., et al., Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing. Carcinogenesis, 2012. 33(7): p. 1270-6. 120. Bhatia, K., et al., Hemi- or homozygosity: a requirement for some but not other p53 mutant proteins to accumulate and exert a pathogenetic effect. Faseb j, 1993. 7(10): p. 951-6. 121. Huang, A., et al., Metabolic alterations and drug sensitivity of tyrosine kinase inhibitor resistant leukemia cells with a FLT3/ITD mutation. Cancer Lett, 2016. 377(2): p. 149-57. 122. Warburg, O., On the Origin of Cancer Cells. Science, 1956. 123(3191): p. 309-314. 123. Basak, N.P. and S. Banerjee, Mitochondrial dependency in progression of acute myeloid leukemia. Mitochondrion, 2015. 21: p. 41-48. 124. Hammoudi, N., et al., Metabolic alterations in cancer cells and therapeutic implications. Chin J Cancer, 2011. 30(8): p. 508-25. 125. Sasca, D., et al., NCAM1 (CD56) promotes leukemogenesis and confers drug resistance in AML. Blood, 2019. 133(21): p. 2305-2319. 126. Chen, B., et al., Reversal of cancer gene expression correlates with drug efficacy and reveals therapeutic targets. Nat Commun, 2017. 8: p. 16022. 127. Nikolova, T., et al., Chloroethylating nitrosoureas in cancer therapy: DNA damage, repair and cell death signaling. Biochim Biophys Acta Rev Cancer, 2017. 1868(1): p. 29-39. 128. Gourd, E., Lomustine in older patients with acute myeloid leukaemia. Lancet Oncol, 2018. 19(11): p. e584. 129. Pigneux, A., et al., Adding lomustine to idarubicin and cytarabine for induction chemotherapy in older patients with acute myeloid leukemia: the BGMT 95 trial results. Haematologica, 2007. 92(10): p. 1327-34. 130. He, W. and H. Hu, BIIB021, an Hsp90 inhibitor: A promising therapeutic strategy for blood malignancies (Review). Oncol Rep, 2018. 40(1): p. 3-15. 131. Powis, G., et al., Wortmannin, a potent and selective inhibitor of phosphatidylinositol-3-kinase. Cancer Res, 1994. 54(9): p. 2419-23. 132. Ihle, N.T., et al., Molecular pharmacology and antitumor activity of PX-866, a novel inhibitor of phosphoinositide-3-kinase signaling. Mol Cancer Ther, 2004. 3(7): p. 763-72. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77287 | - |
| dc.description.abstract | 急性骨髓性白血病(AML)的病人中，大約有20~30%帶有FLT3基因突變，其中以FLT3之內部串聯重複(FLT3-ITD)最為常見，且具較差的預後，因此近年來成為熱門的AML研究標的。雖然FLT3標靶藥物初期的治療成效可見，但是大多只能使病人得到暫時緩解，病人對治療產生抗性並復發的機率仍高。目前臨床上對於FLT3標靶藥物產生抗藥性的原因仍眾說紛紜，因此有必要持續探討其抗藥機制並發展新穎的治療策略。
在過去實驗室的研究，FLT3標靶藥物cabozantinib (CBZ)可以在低濃度下選擇性的減緩帶有FLT3-ITD之AML細胞株Molm13及MV4-11生長，並抑制FLT3下游的訊息傳遞；另外在小鼠動物實驗中也能有效抑制MV4-11以及Molm13皮下腫瘤的生長。為了探討AML細胞對CBZ抗藥性的相關機轉，實驗室也建立了對於CBZ具有抗藥性的細胞株Molm13-XR以及MV4-11-XR。 現今次世代定序技術發達，RNA-seq為熱門的轉錄體學研究工具，透過RNA-seq的分析，我們可以瞭解生物體內是否有新穎的點突變或融合基因的存在，也可以偵測大量基因的表達量，並結合許多現有的生物資訊工具，進行路徑詮釋或找尋具有治療潛力的小分子藥物。因此本篇研究利用生物資訊工具對兩株抗藥細胞Molm13-XR以及MV4-11-XR在點突變、融合基因以及基因表達量進行抗藥性的探討，並藉此尋找有潛力逆轉抗藥細胞基因表達的小分子藥物，也以細胞實驗以及斑馬魚動物實驗確認其效果、進行驗證。 本篇研究確認Molm13-XR與MV4-11-XR皆增加FLT3 D835Y點突變，且MV4-11-XR為同型合子；另外也初步在兩株抗藥細胞整理出共同出現的60個基因具有SNP以及20個基因具有小片段插入刪去(indel)。在融合基因分析上，我們雖未發現與抗藥性有關的融合基因，但特定融合基因的表達量在母株細胞及抗藥細胞的差異可能暗示著抗藥細胞產生時存在篩選的效應(clone selection)。在基因表達量分析上，利用KEGG及DAVID進行路徑詮釋後，結果顯示兩株細胞皆有JAK-STAT、GPCR等致癌訊息路徑的過度活化，以及在醣類、胺基酸或脂質代謝路徑的基因表達量上升，與實驗室先前研究發現抗藥細胞能量代謝特性的變化相互呼應。 透過分別比對兩株抗藥細胞株中代謝相關基因表達量的變化，我們利用Connectivity map找尋具有潛力改變細胞代謝特性而克服抗藥性的小分子藥物。在Molm13-XR中，我們發現化療藥物lomustine以及HSP90抑制劑radicicol與tanespimycin；以及在MV4-11-XR中有mTOR抑制劑rapamycin以及其他PI3K/mTOR抑制劑，皆具有逆轉細胞代謝特性以及克服抗藥性的潛力。實驗結果指出，lomustine、radicicol可以抑制細胞糖解相關基因的表達以及葡萄糖攝取的能力；而radicicol更能夠進一步抑制乳酸的生成，且可能透過抑制FLT3訊息傳遞路徑來調控HIF-1α、MYC及MCL-1，影響細胞的代謝與存活。另外，我們也使用斑馬魚異種移植模型來驗證前述的實驗，結果顯示合併radicicol與cabozantinib可以有效降低斑馬魚體內的AML細胞量。我們的實驗結果認為，利用生物資訊工具找尋小分子藥物用以逆轉細胞代謝特性，或為可行的治療策略來克服對FLT3-ITD AML細胞對CBZ之抗藥性。 | zh_TW |
| dc.description.abstract | Internal tandem duplication of FLT3 (FLT3-ITD) was found in about 20-30% in AML patients and resulting in poor prognosis. Hence, FLT3 have thought to be an ideal target for AML treatment. Although FLT3 targeted therapy showed modest promising effect in the initial stage, relapse and drug resistance occurred in most patients, which indicated the importance of exploring the resistant mechanisms and discovering novel treatment strategies.
Previously, we showed that cabozantinib(CBZ), an oral multi-targeted tyrosine kinase inhibitor, could be selectively cytotoxic in AML cells with FLT3-ITD. However, drug resistance occurred after gradual escalating concentration of CBZ incubation of the FLT3-ITD-harboring Molm13 and MV4-11 cells, with IC50 increased from 1.06 nM of parental Molm13 cells to 473.36 nM of the resistant Molm13-XR cells, and from 9.5 nM of parental MV4-11 cells to 1500 nM of resistant MV4-11-XR. In this research, we used RNA-seq to discover SNVs, fusion genes and signaling pathways changed in cabozantinib resistant cells. Connectivity map was used to predict small molecules which had potentials to reverse gene expression in resistant cells. Also, glucose uptake and lactate production were measured to realize the metabolic alternations after drug treatments. Zebrafish xenograft experiments were performed to evaluate the drug efficacy in vivo. We found FLT3 D835Y mutants and other 60 SNVs and 20 indels occurred in both CBZ-resistant cell lines. Pathway analysis showed that metabolic alternation on glucose, amino acid and lipid, GPCR pathway and JAK-STAT pathway activation were common features of these two resistant cell lines. Connectivity map predicted that lomustine, HSP90 inhibitor radicicol, and tanespimycin had potentials to reverse the metabolic phenotypes in Molm13-XR cells; and also showed that PI3K/mTOR inhibitor rapamycin, gedatolisib, and omipalisib could reverse that on MV4-11-XR. Data showed that lomustine and radicicol could reduce glycolysis-related genes expression and glucose uptake; Radicicol could also inhibit lactate production and may regulate cell metabolism and survival through inhibition of FLT3 downstream signaling to decrease the protein level of HIF-1α, MYC, and MCL-1. Finally, a combination of radicicol and cabozantinib could effectivity reduce tumor burden in zebrafish xenograft model. In this study, we showed reverse metabolic gene expression and phenotype with small molecules predicted by bioinformatic tools could be a powerful way to discover novel compounds to overcome cabozantinib-resistance in FLT3-ITD leukemia cells. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-10T21:54:17Z (GMT). No. of bitstreams: 1 ntu-108-R06424012-1.pdf: 6164453 bytes, checksum: a6d5a979ae3b5e7d9f0dd535fe5cc69f (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 致謝 i
摘要 ii Abstract iv 目錄 vi 圖目錄 x 表目錄 xi 縮寫表 xii 第一章 前言 1 1.1. 急性骨髓性白血病簡介 1 1.1.1. 急性骨髓性白血病(Acute Myeloid Leukemia, AML) 1 1.1.2. AML之分類 1 1.1.3. AML之治療 1 1.2. FLT3 3 1.2.1. FLT3簡介 3 1.2.2. FLT3突變 3 1.2.3. FLT3標靶藥物簡介 4 1.3. cabozantinib (CBZ)簡介 5 1.4. 抗藥性細胞株Molm13-XR之簡介 5 1.5. 抗藥性細胞株MV4-11-XR之簡介 6 1.6. Gene Set Enrichment Analysis(GSEA)簡介 6 1.7. Connectivity map簡介 7 1.8. 代謝路徑介紹 8 1.8.1. Warburg effect 簡介 8 1.8.2. Pentose phosphate pathway (PPP) 8 1.9. lomustine簡介 9 1.10. HSP90及HSP90抑制劑簡介 9 1.11. PI3K/mTOR抑制劑簡介 9 1.12. 斑馬魚 10 第二章 研究目的 12 第三章 材料與方法 13 3.1. 材料 13 3.1.1. 細胞株 13 3.1.2. 斑馬魚 13 3.1.3. 儀器設備 13 3.1.4. 藥品 14 3.1.5. 使用的小分子藥物 16 3.1.6. 抗體 16 3.1.7. 試劑組 17 3.1.8. 藥品與試劑配製 17 3.1.9. 生物資訊分析工具與軟體 19 3.2. 方法 20 3.2.1. 細胞培養 20 3.2.2. 細胞抑殺試驗(MTS assay) 20 3.2.3. 葡萄糖攝取試驗(glucose uptake) 20 3.2.4. 乳酸產量(lactate production assay) 21 3.2.5. ATP含量測定(ATP assay) 21 3.2.6. 細胞內蛋白質萃取 22 3.2.7. 蛋白質濃度定量 22 3.2.8. 西方墨點法 22 3.2.9. RNA萃取 23 3.2.10. 反轉錄聚合酶反應(reverse transcription) 23 3.2.11. 聚合酶連鎖反應(polymerase chain reacction, PCR) 24 3.2.12. 洋菜膠電泳分析(agarose gel electrophoresis) 24 3.2.13. 聚合酶連鎖反應產物純化(clean-up) 25 3.2.14. PCR 產物序列分析(sequencing) 25 3.2.15. 即時監控聚合酶連鎖反應(q-PCR) 25 3.2.16. 斑馬魚藥物毒性試驗 26 3.2.17. 慢病毒轉染細胞(lentivirus transduction) 26 3.2.18. 斑馬魚異種移植 26 3.2.19. RNA-seq 分析 26 3.2.20. 統計方法 28 第四章 實驗結果 29 4.1. 針對具有cabozantinib (CBZ)之抗性之細胞進行點突變分析 29 4.1.1. Molm13-XR及MV4-11-XR在FLT3下游基因的突變情形 29 4.1.2. Molm13-XR及MV4-11-XR 在TP53的突變情形 29 4.1.3. Molm13-XR及MV4-11-XR 在AML常見變異基因分析 30 4.1.4. 在Molm13-XR 及 MV4-11-XR共有的SNP及indel 30 4.2. 針對具有CBZ抗性之細胞進行融合基因分析 30 4.2.1. Molm13-P與Molm13-XR融合基因的分析 31 4.2.2. MV4-11-P與MV4-11-XR融合基因的分析 32 4.3. 針對具有CBZ抗性之細胞進行基因表達量分析 32 4.3.1. 利用DAVID分析抗藥細胞具有差異之訊息傳遞路徑 33 4.3.2. 利用GSEA分析抗藥細胞具有差異之訊息傳遞路徑 33 4.3.3. 以火山圖呈現顯著差異表達基因中與代謝有關的基因 33 4.4. 利用connectivity map 找尋具有逆轉細胞代謝特性之小分子藥物 33 4.4.1. 有潛力逆轉Molm13-XR細胞代謝特性之小分子藥物 34 4.4.2. 有潛力逆轉MV4-11-XR細胞代謝特性之小分子藥物 34 4.5. lomustine (CCNU)毒殺Molm13-XR的作用 34 4.5.1. CCNU對Molm13-P及Molm13-XR的抑制效果 34 4.5.2. CCNU對糖解作用的影響 35 4.6. 利用HSP90抑制劑-radicicol對Molm13-XR的作用 35 4.6.1. radicicol/tanespimycin 對Molm13-XR的抑制效果 35 4.6.2. radicicol對糖解作用的影響 36 4.6.3. radicicol對細胞產能速率的影響 36 4.6.4. radicicol對細胞糖解相關分子蛋白量的影響 36 4.6.5. radicicol對FLT3下游訊息傳遞分子的影響 37 4.7. 利用PI3K/mTOR抑制劑對MV4-11-XR的作用 37 4.7.1. 數種PI3K/mTOR抑制劑對MV4-11-P及MV4-11-XR的抑制效果 37 4.7.2. 數種PI3K/mTOR抑制劑對糖解作用的抑制效果 38 4.8. 斑馬魚異體移植之動物模型 38 4.8.1. 斑馬魚藥物毒性試驗 38 4.8.2. 以藥物處理斑馬魚異體移植腫瘤 39 第五章 討論 40 第六章 參考文獻 45 圖 54 表 76 附圖 92 附表 101 | |
| dc.language.iso | zh-TW | |
| dc.title | 探討急性骨髓性白血病細胞對cabozantinib抗藥機制─從生物資訊到實驗室分析 | zh_TW |
| dc.title | Exploring cabozantinib-resistance in AML-from bioinformatics to bench | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 胡忠怡(Chung-Yi Hu),歐大諒(Da-Liang Ou),顧雅真(Ya-Chen Ko),侯信安(Hsin-An Hou) | |
| dc.subject.keyword | 急性骨髓性白血病,FLT3-ITD,cabozantinib抗藥性,lomustine,radicicol, | zh_TW |
| dc.subject.keyword | AML,FLT3-ITD,cabozantinib resistance,lomustine,radicicol, | en |
| dc.relation.page | 103 | |
| dc.identifier.doi | 10.6342/NTU201902963 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2019-08-12 | |
| dc.contributor.author-college | 醫學院 | zh_TW |
| dc.contributor.author-dept | 醫學檢驗暨生物技術學研究所 | zh_TW |
| 顯示於系所單位： | 醫學檢驗暨生物技術學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-R06424012-1.pdf 目前未授權公開取用 | 6.02 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。