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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 莊曜宇(Eric Y. Chuang) | |
dc.contributor.author | Feng-Ming Hsu | en |
dc.contributor.author | 許峰銘 | zh_TW |
dc.date.accessioned | 2021-06-15T11:33:13Z | - |
dc.date.available | 2021-08-30 | |
dc.date.copyright | 2016-08-30 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-08-16 | |
dc.identifier.citation | 1. Ferlay J, Soerjomataram I, Ervik M, et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11. Lyon, France: International Agency for Research on Cancer. 2013; http://globocan.iarc.fr.
2. Siewert JR, Ott K. Are squamous and adenocarcinomas od the esophagus the same disease? Semin Radiat Oncol 2007;17:38–44. 3. Melhado RE, Alderson D, Tucker O. The changing face of esophageal cancer. Cancers (Basel) 2010;2:1379–1404. 4. Gupta B, Kumar N. Worldwide incidence, mortality and time trends for cancer of the oesophagus. Eur J Cancer Prev 2016 [Epub ahead of print]. 5. Chiang CJ, Chen YC, Chen CJ, You SL, Lai MS; Taiwan Cancer Registry Task Force. Cancer trends in Taiwan. Jpn J Clin Oncol 2010;40:897–904. 6. Enzinger PC, Mayer RJ. Esophageal cancer. N Engl J Med 2003;349:2241–2252. 7. Gebski V, Burmeister B, Smithers BM, Foo K, Zalcberg J, Simes J; Australasian Gastro-Intestinal Trials Group. Survival benefits from neoadjuvant chemoradiotherapy or chemotherapy in oesophageal carcinoma: a meta-analysis. Lancet Oncol 2007;8:226–234. 8. Burmeister BH, Smithers BM, Gebski V, Fitzgerald L, Simes RJ, Devitt P, et al. Surgery alone versus chemoradiotherapy followed by surgery for resectable cancer of the oesophagus: a randomized controlled phase III trial. Lancet Oncol 2005;6:659–668. 9. van Hagen P, Hulshof MC, van Lanschot JJ, Steyerberg EW, van Berge Henegouwen MI, Wijnhoven BP, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med 2012;366:2074–2084. 10. Cooper JS, Guo MD, Herskovic A, Macdonald JS, Martenson JA Jr, Al-Sarraf M, et al. Chemoradiotherapy of locally advanced esophageal cancer: long-term follow-up of a prospective randomized trial (RTOG 85-01). Radiation Therapy Oncology Group. JAMA 1999;281:1623–1627. 11. Stahl MS, Stuschke M, Lehmann N, Meyer HJ, Walz MK, Seeber S, et al. Chemoradiation with and without surgery in patients with locally advanced squamous cell carcinoma of the esophagus. J Clin Oncol 2005;23:2310–2317. 12. Bedenne L, Michel P, Bouché O, Milan C, Mariette C, Conroy T, et al. Chemoradiation followed by surgery compared with chemoradiation alone in squamous cancer of the esophagus: FFCD 9102. J Clin Oncol 2007;25:1160–1168. 13. Shapiro J, van Lanschot JJ, Hulshof MC, van Hagen P, van Berge Henegouwen MI, Wijnhoven BP, et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomized controlled trial. Lancet Oncol 2015;16:1090–1098. 14. Berger AC, Farma J, Scott WJ, Freedman G, Weiner L, Cheng JD, et al. Complete response to neoadjuvant chemoradiothearpy in esophageal carcinoma is associated with significantly improved survival. J Clin Oncol 2005;23:4330–4337. 15. Wang CC, Cheng JC, Tsai CL, Lee JM, Huang PM, Lin CC, et al. Pathological stage after neoadjuvant chemoradiation and esophagectomy superiorly predicts survival in patients with esophageal squamous cell carcinoma. Radiother Oncol 2015;115:9–15. 16. Guo JC, Huang TC, Lin CC, Hsieh MS, Chang CH, Huang PM, et al. Postchemoradiotherapy pathologic stage classified by the American Joint Committee on the Cancer Staging System predicts prognosis of patients with locally advanced esophageal squamous cell carcinoma. J Thorac Oncol 2015;10:1481–1489. 17. Schneider PM, Baldus SE, Metzger R, Kocher M, Bongartz R, Bollschweiler E, et al. Histomorphologic tumor regression and lymph node metastases determine prognosis following neoadjuvant radiochemotherapy for esophageal cancer: implications for response classification. Ann Surg 2005;242:684–692. 18. Tong DK, Law S, Kwong DL, Chan KW, Lam AK, Wong KH. Histological regression of squamous esophageal carcinoma assessed by percentage of residual viable cells after neoadjuvant chemoradiation is an important prognostic factor. Ann Surg Oncol 2010;17:2184–2192. 19. Donohoe CL, O’Farrell NJ, Grant T, King S, Clarke L, Muldoon C, et al. Classification of pathologic response to neoadjuvant therapy in esophageal and junctional cancer: assessment of existing measures and proposal of a novel 3-point standard. Ann Surg 2013;258:784–792. 20. Hsu FM, Lin CC, Lee JM, Chang YL, Hsu CH, Tsai YC, et al. Improved local control by surgery and paclitaxel-based chemoradiation for esophageal squamous cell carcinoma: results of a retrospective non-randomized study. J Surg Oncol 2008;98:34–41. 21. Chao YK, Chan SC, Liu YH, Chen HW, Wan YL, Chang HK, et al. Pretreatment T3-4 stage is an adverse prognostic factor in patients with esophageal squamous cell carcinoma who achieve pathological complete response following preoperative chemoradiotherapy. Ann Surg 2009;249:392–396. 22. Bonnetain F, Bouché O, Michel P, Mariette C, Conroy T, Pezet D, et al. A comparative longitudinal quality of life study using the Spitzer quality of life index in a randomized multicenter phase III trial (FFCD 9102): chemoradiation followed by surgery compared with chemoradiation alone in locally advanced squamous resectable thoracic esophageal cancer. Ann Oncol 2006;17:827–834. 23. Merritt RE, Whyte RI, D’Arcy NT, Hoang CD, Shrager JB. Morbidity and mortality after esophagectomy following neoadjuvant chemoradiation. Ann Thorac Surg 2011;92:2034–2040. 24. Wang H, Shen Y, Feng M, Zhang Y, Jiang W, Xu S, et al. Outcomes, quality of life, and survival after esophagectomy for squamous cell carcinoma: A propensity score-matched comparison of operative approaches. J Thorac Cardiovasc Surg 2015;149:1006–1014. 25. Vincent J, Mariette C, Pezet D, Huet E, Bonnetain F, Bouché O, et al. Early surgery for failure after chemoradiation in operable thoracic oesophageal cancer. Analysis of the non-randomised patients in FFCD 9102 phase III trial: Chemoradiation followed by surgery versus chemoradiation alone. Eur J Cancer 2015;51:1683–1693. 26. Gillham CM, Reynolds J, Hollywood D. Predicting the response of localized oesophageal cancer to neo-adjuvant chemoradiation. World J Surg Oncol 2007;5:97. 27. Malik V, Lucey JA, Duffy GJ, Wilson L, McNamara L, Keogan M, et al. Early repeated 18F-FDG PET scans during neoadjuvant chemoradiation fail to predict histopathologic response or survival benefit in adenocarcinoma of the esophagus. J Nucl Med 2010;51:1863–1869. 28. van Heijl M, Omloo JM, van Berge Henegouwen MI, Hoekstra OS, Boellaard R, Bossuyt PM, et al. Fluorodeoxyglucose positron emission tomography for evaluating early response during neoadjuvant chemoradiotherapy in patients with potentially curable esophageal cancer. Ann Surg 2011;253:56–63. 29. Ajani JA, Correa AM, Hofstetter WL, Rice DC, Suzuki A, Taketa T, et al. Clinical parameters model for predicting pathologic complete response following preoperative chemoradiation in patients with esophageal cancer. Ann Oncol 2012;23:2638–2642. 30. Lin SH, Wang J, Allen PK, Correa AM, Maru DM, Swisher SG, et al. A nomogram that predicts pathological complete response to neoadjuvant chemoradiation also predicts survival outcomes after definitive chemoradiation for esophageal cancer. J Gastreointest Oncol 2015;6:54–52. 31. Song Y, Li L, Ou, Y, Gao Z, Li E, Li X, et al. Identification of genomic alterations in oesophageal quamous cell cancer. Nature 2014;509:91–95. 32. Lin DC, Hao JJ, Nagata Y, Xu L, Shang L, Meng X, et al. Genomic and molecular characterization of esophageal squamous cell carcinoma. Nat Genet 2014;46:467–473. 33. Gao YB, Chen ZL, Li JG, Hu XD, Shi XJ, Sun ZM, et al. Genetic landscape of esophageal squamous cell carcinoma. Nat Genet 2014;46:1097–1102. 34. Zhang L, Zhou Y, Cheng C, Cui H, Cheng L, Kong P, et al. Genomic analyses reveal mutational signatures and frequently altered genes in esophageal squamous cell carcinoma. Am J Hum Genet 2015;96:597–611. 35. Cheng C, Cui H, Zhang L, Jia Z, Song B, Wang F, et al. Genomic analyses reveal FAM84B and the NOTCH pathway are associated with the progression of esophageal squamous cell carcinoma. Gigascience. 2016;5:1. 36. Qin HD, Liao XY, Chen YB, Huang SY, Xue WQ, Li FF, et al. Genomic Characterization of Esophageal Squamous Cell Carcinoma Reveals Critical Genes Underlying Tumorigenesis and Poor Prognosis. Am J Hum Genet 2016;98:709–727. 37. Zack TI, Schumacher SR, Carter SL, Cherniack AD, Saksena G, Tabak B, et al. Pan-cancer patterns of somatic copy number alteration. Nat Genet 2013;45:1134–1140. 38. Teo SM, Pawitan Y, Ku CS, Chia KS, Salim A. Statistical challenges associated with detecting copy number variations with next-generation sequencing. Bioinformatics 2012;28:2711–2718. 39. Kang X, Chen K, Li Y, Li J, D’Amico TA, Chen X. Personalized targeted therapy for esophageal squamous cell carcinoma. World J Gastroenterol 2015;21:7648–7658 40. Crosby T, Hurt CN, Falk S, Gollins S, Mukherjee S, Staffurth J, et al. Chemoradiotherapy with or without cetuximab in patients with oesophageal cancer (SCOPE1): a multicentre, phase 2/3 randomised trial. Lancet Oncol 2013;14:627–637. 41. Cao W, Wu W, Yan M, Tian F, Ma C, Zhang Q, et al. Multiple region whole-exome sequencing reveals dramatically evolving intratumor genomic heterogeneity in esophageal squamous cell carcinoma. Oncogenesis. 2015;4:e175. 42. Luthra R, Wu TT, Luthra MG, Izzo J, Lopez-Alvarez E, Zhang L, et al. Gene expression profiling of localized esophageal carcinomas: association with pathologic response to preoperative chemoradiation. J Clin Oncol 2006;24:259–267. 43. Maher SG, Gillham CM, Duggan SP, Smyth PC, Miller N, Muldoon C, et al. Gene expression analysis of diagnostic biopsies predicts pathological response to neoadjuvant chemoradiotherapy of esophageal cancer. Ann Surg 2009;250:729–737. 44. Ko MA, Zehong G, Virtanen C, Guindi M, Waddell TK, Keshavjee S, et al. MicroRNA expression profiling of esophageal cancer before and after induction chemoradiotherapy. Ann Thorac Surg 2012;94:1094–1102. 45. Wen J, Yang H, Liu MZ, Luo KJ, Liu H, Hu Y, et al. Gene expression analysis of pretreatment biopsies predicts the pathological response of esophageal squamous cell carcinomas to neo-chemoradiotherapy. Ann Oncol 2014;25:1769–1774. 46. Koshy M, Greenwald BD, Hausner P, Krasna MJ, Horiba N, Battafarano RJ, et al. Outcomes after trimodality therapy for esophageal cancer: the impact of histology on failure patterns. Am J Clin Oncol 2011;34:259–264. 47. Ashida A, Boku N, Aoyagi K, Sato H, Tsubosa Y, Minashi K, et al. Expression profiling of esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy: clinical implications. Int J Oncol 2006;28:1345–1352. 48. Oshita F, Sekiyama A, Saito H, Yamada K, Noda K, Miyagi Y. Genome-wide cDNA microarray screening of genes related to the benefits of paclitaxel and irinotecan chemotherapy in patients with advanced non-small cell lung cancer. J Exp Ther Oncol 2006;6:49–53. 49. Maher SG, McDowell DT, Collins BC, Muldoon C, Gallagher WM, Reynolds JV. Serum proteomic profiling reveals that pretreatment complement protein levels are predictive of esophageal cancer patient response to neoadjuvant chemoradiation. Ann Surg 2011;254:809–816. 50. Chen PC, Chen YC, Lai LC, Tsai MH, Chen SK, Yang PW, et al. Use of germline polymorphisms in predicting concurrent chemoradiotherapy response in esophageal cancer. Int J Radiat Oncol Biol Phys 2012;82:1996–2003. 51. Tanaka K, Yano M, Motoori M, Kishi K, Miyashiro I, Shingai T, et al. CEA-antigen and SCC-antigen mRNA expression in peripheral blood predict hematogenous recurrence after resection in patients with esophageal cancer. Ann Surg Oncol 2010;17: 2779–2786. 52. Hoffmann AC, Vallböhmer D, Grimminger P, Metzger R, Prenzel KL, Hoelscher AH, et al. Preoperative survivin mRNA detection in peripheral blood is an independent predictor of outcome in esophageal carcinoma. Pharmacogenomics 2010;11:341–347. 53. Cheng JC, Graber MS, Hsu FM, Tsai CL, Castaneda L, Lee JM, et al. High serum levels of vascular endothelial growth factor-A and transforming growth factor-β1 before neoadjuvant chemoradiotherapy predict poor outcomes in patients with esophageal squamous cell carcinoma receiving combined modality therapy. Ann Surg Oncol 2014;21:2361–2368. 54. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. PNAS 2001;98:5116–5121. 55. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003;4:P3. 56. Ishwaran H, Rao JS, Kogalur UB. BAMarray™: Java software for Bayesian analysis of variance for microarray data. BMC Bioinformatics 2006;7:59. 57. Ishwaran H, Rao JS. Detecting differentially expressed genes in microarrays using Bayesian model selection. J Amer Statist Assoc 2003;98:438–455. 58. Miller WR, Larionov A, Renshaw L, Anderson TJ, Walker JR, Krause A, et al. Gene expression profiles differentiating between breast cancers clinically responsive or resistant to letrozole. J Clin Oncol 2009;27:1382–1387. 59. Brabender J, Vallböhmer D, Grimminger P, Hoffmann AC, Ling F, Lurje G, et al. ERCC1 RNA expression in peripheral blood predicts minor histopathological response to neoadjuvant radio-chemotherapy in patients with locally advanced cancer of the esophagus. J Gastrointest Surg 2008;12:1815–1821. 60. Warnecke-Eberz U, Metzger R, Miyazono F, Baldus SE, Neiss S, Brabender J, et al. High specificity of quantitative excision repair cross-complementing 1 messenger RNA expression for prediction of minor histopathological response to neoadjuvant radiochemotherapy in esophageal cancer. Clin Cancer Res 2004;10: 3794–3799. 61. Adam PJ, Boyd R, Tyson KL, Fletcher GC, Stamps A, Hudson L, et al. Comprehensive proteomic analysis of breast cancer cell membranes reveals unique proteins with potential roles in clinical cancer. J Biol Chem 2003;278:6482–6489. 62. Ghoussaini M, Al Olama AA, Kote-Jarai Z, Driver KE, et al. Multiple loci with different cancer specificities within the 8q24 gene desert. J Natl Cancer Inst 2008;100:962–966. 63. Huang XP, Rong TH, Wang JY, Tang YQ, Li BJ, Xu DR, et al. Negative implication of C-MYC as an amplification target in esophageal cancer. Cancer Genet Cytogenet 2006;165:20–24. 64. van Duin M, van Marion R, Vissers K, Watson JE, van Weerden WM, Schröder FH, et al. High-resolution array comparative genomic hybridization of chromosome 8q: evaluation of putative progression markers for gastroesophageal junction adenocarcinomas. Cytogenet Genome Res 2007;118:130–137. 65. Taylor PR, Abnet CC, and Dawsey SM. Squamous dysplasia—the precursor lesion for esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev 2013;22:540–552. 66. Ueno T, Tangoku A, Yoshino S, Abe T, Hayashi H, Toshimitsu H, et al. Prediction of nodal metastasis by comparative genomic hybridization in biopsy specimens from patients with superficial esophageal squamous cell carcinoma. Clin Cancer Res 2003;9:513751–41. 67. Hu N, Wang C, Ng D, Clifford R, Yang HH, Tang ZZ, et al. Genomic characterization of esophageal squamous cell carcinoma from a high-risk population in China. Cancer Res 2009;69:5908–17. 68. Miyawaki Y, Kawachi H, Ooi A, Eishi Y, Kawano T, Inazawa J, et al. Genomic copy-number alterations of MYC and FHIT genes are associated with survival in esophageal squamous-cell carcinoma. Cancer Sci 2012;103:1558–1566. 69. Hao JJ, Shi ZZ, Zhao ZX, Zhang Y, Gong T, Li CX, et al. Characterization of genetic rearrangements in esophageal squamous carcinoma cell lines by a combination of M-FISH and array-CGH: further confirmation of some split genomic regions in primary tumors. BMC Cancer 2012;12:367. 70. Brown J, Bothma H, Veale R, Willem P. Genomic imbalances in esophageal carcinoma cell lines involve Wnt pathway genes. World J Gastroenterol 2011;17:2909–2923. 71. Camps J, Nguyen QT, Padilla-Nash HM, Knutsen T, McNeil NE, Wangsa D, et al. Integrative genomics reveals mechanisms of copy number alterations responsible for transcriptional deregulation in colorectal cancer. Genes Chromosomes Cancer 2009;48:1002–1017. 72. Hu Z, Zhu D, Wang W, Li W, Jia W, Zeng X, et al. Genome-wide profiling of HPV integration in cervical cancer identifies clustered genomic hot spots and a potential microhomology-mediated integration mechanism. Nat Genet 2015;47:158–163. 73. Solé X, Hernández P, de Heredia ML, Armengol L, Rodríguez-Santiago B, Gómez L, et al. Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility. BMC Genomics 2008;9:12. 74. Ji W, Bian Z, Yu Y, Yuan C, Liu Y, Yu L, et al. Expulsion of micronuclei containing amplified genes contributes to a decrease in double minute chromosomes from malignant tumor cells. Int J Cancer 2014;134:1279–1288. 75. Parisi F, Ariyan S, Narayan D, Bacchiocchi A, Hoyt K, Cheng E, et al. Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies. BMC Genomics 2011;12:230. 76. Yamaga R, Ikeda K, Horie-Inoue K, Ouchi Y, Suzuki Y, Inoue S. RNA sequencing of MCF-7 breast cancer cells identifies novel estrogen-responsive genes with functional estrogen receptor-binding sites in the vicinity of their transcription start sites. Horm Cancer 2013;4:222–232. 77. Song D, Chaerkady R, Tan AC, García-García E, Nalli A, Suárez-Gauthier A, et al. Antitumor activity and molecular effects of the novel heat shock protein 90 inhibitor, IPI-504, in pancreatic cancer. Mol Cancer Ther 2008;7:3275–3284. 78. Ciuffreda L, Del Bufalo D, Desideri M, Di Sanza C, Stoppacciaro A, Ricciardi MR, et al. Growth-inhibitory and antiangiogenic activity of the MEK inhibitor PD0325901 in malignant melanoma with or without BRAF mutations. Neoplasia 2009;11:720–731. 79. Nodale C, Sheffer M, Jacob-Hirsch J, Folgiero V, Falcioni R, Aiello A, et al. HIPK2 downregulates vimentin and inhibits breast cancer cell invasion. Cancer Biol Ther 2012;13:198–205. 80. Arroyo R, Suñé G, Zanzoni A, Duran-Frigola M, Alcalde V, Stracker TH, et al. Systematic identification of molecular links between core and candidate genes in breast cancer. J Mol Biol 2015;427:1436–1450. 81. Huang X, Di Liberto M, Jayabalan D, Liang J, Ely S, Bretz J, et al. Prolonged early G1 arrest by selective CDK4/CDK6 inhibition sensitizes myeloma cells to cytotoxic killing through cell cycle–coupled loss of IRF4. Blood 2012;120:1095–1106. 82. Ji H, Wang J, Fang B, Fang X, Lu Z. α-Catenin inhibits glioma cell migration, invasion, and proliferation by suppression of β-catenin transactivation. J Neurooncol 2011;103:445–451. 83. Xu ZY, Loignon M, Han FY, Panasci L, Aloyz R. Xrcc3 induces cisplatin resistance by stimulation of Rad51-related recombinational repair, S-phase checkpoint activation, and reduced apoptosis. J Pharmacol Exp Ther 2005;314:495–505. 84. Gildemeister OS, Sage JM, Knight KL. Cellular redistribution of Rad51 in response to DNA damage: novel role for Rad51C. J Biol Chem 2009;284:31945–1952. 85. Slupianek A, Schmutte C, Tombline G, Nieborowska-Skorska M, Hoser G, Nowicki MO, et al. BCR/ABL regulates mammalian RecA homologs, resulting in drug resistance. Mol Cell 2001;8:795–806. 86. Hsu FM, Cheng JC, Chang YL, Lee JM, Koong AC, Chuang EY. Circulating mRNA profiling in esophageal squamous cell carcinoma identifies FAM84B as a biomarker in predicting pathological response to neoadjuvant chemoradiation. Sci Rep 2015;5:10291. 87. McConnell BB, Ghaleb AM, Nandan MO, Yang VW. The diverse functions of Krüppel-like factors 4 and 5 in epithelial biology and pathobiology. Bioessays 2007;29:549–557. 88. Yang Y, Goldstein BG, Chao HH, Katz JP. KLF4 and KLF5 regulate proliferation, apoptosis and invasion in esophageal cancer cells. Cancer Biol Ther 2005;4:1216–1221. 89. He H, Li S, Hong Y, Zou H, Chen H, Ding F, et al. Krüppel-like factor 4 promotes esophageal squamous cell carcinoma differentiation by up-regulating keratin 13 expression. J Biol Chem 2015;29:13567–13577. 90. Goldstein BG, Chao HH, Yang Y, Yermolina YA, Tobias JW, Katz JP. Overexpression of Kruppel-like factor 5 in esophageal epithelia in vivo leads to increased proliferation in basal but not suprabasal cells. Am J Physiol Gastrointest Liver Physiol 2007;292,:G1784–1792. 91. Yang Y, Nakagawa H, Tetreault MP, Billig J, Victor N, Goyal A, et al. Loss of transcription factor KLF5 in the context of p53 ablation drives invasive progression of human squamous cell cancer. Cancer Res 2011;71:6475–6484. 92. Tarapore RS, Yang Y, and Katz JP. Restoring KLF5 in esophageal squamous cell cancer cells activates the JNK pathway leading to apoptosis and reduced cell survival. Neoplasia 2013;15:472–480. 93. Bell SM, Zhang L, Mendell A, Xu Y, Haitchi HM, Lessard JL, et al. Kruppel-like factor 5 is required for formation and differentiation of the bladder urothelium. Dev Biol 2011;358:79–90. 94. Luo A, Kong J, Hu G, Liew CC, Xiong M, Wang X, et al. Discovery of Ca2+-relevant and differentiation-associated genes downregulated in esophageal squamous cell carcinoma using cDNA microarray. Oncogene 2004;23:1291–1299. 95. Lehman HL, Yang X, Welsh PA, Stairs DB. P120-catenin down-regulation and epidermal growth factor receptor overexpression results in a transformed epithelium that mimics esophageal squamous cell carcinoma. Am J Pathol 2015;185:240–251. 96. Hajra KM, Fearon ER. Cadherin and catenin alterations in human cancer. Genes Chromosomes Cancer 2002;34:255–268. 97. Benjamin JM, Nelson WJ. Bench to bedside and back again: molecular mechanisms of alpha-catenin function and roles in tumorigenesis. Semin Cancer Biol 2008;18:53–64. 98. Vasioukhin V, Bauer C, Degenstein L, Wise B, Fuchs E. Hyperproliferation and defects in epithelial polarity upon conditional ablation of alpha-catenin in skin. Cell 2001;104:605–617. 99. Setoyama T, Natsugoe S, Okumura H, Matsumoto M, Uchikado Y, Yokomakura N, et al. alpha-catenin is a significant prognostic factor than E-cadherin in esophageal squamous cell carcinoma. J Surg Oncol 2007;95:148–155. 100. Troyanovsky RB, Klingelhöfer J, Troyanovsky SM. Α-Catenin contributes to the strength of E-cadherin-p120 interactions. Mol Biol Cell 2011;22:4247–4255. 101. Piedra J, Miravet S, Castaño J, Pálmer HG, Heisterkamp N, García de Herreros A, et al. p120 Catenin-associated Fer and Fyn tyrosine kinases regulate β-catenin Tyr-142 phosphorylation and β-catenin-α-catenin interaction. Mol Cell Biol 2003;23:2287–2297. 102. Liu SC, Bassi DE, Zhang SY, Holoran D, Conti CJ, Klein-Szanto AJ. Overexpression of cyclin D2 is associated with increased in vivo invasiveness of human squamous carcinoma cells. Mol Carcinog 2002;34:131–139. 103. Rojas P, Cadenas MB, Lin PC, Benavides F, Conti CJ, Rodriguez-Puebla ML. Cyclin D2 and cyclin D3 play opposite roles in mouse skin carcinogenesis. Oncogene. 2007;26:1723–1730 104. McDonald WH, Pavlova Y, Yates JR, Boddy MN. Novel essential DNA repair proteins Nse1 and Nse2 are subunits of the fission yeast Smc5–Smc6 complex. J Biol Chem 2003;278:45460–45467. 105. Potts PR, Yu H. Human MMS21/NSE2 is a SUMO ligase required for DNA repair. Mol Cell Biol 2005;25:7021–7032. 106. Arroyo R. A network biology approach to breast and colorectal cancers. 2014; PhD dissertation, Universitat de Barcelona, 244 pages. (http://diposit.ub.edu/dspace/handle/2445/55832) 107. Masud Karim SM, Liu L, Le TD, Li J. Identification of miRNA-mRNA regulatory modules by exploring collective group relationships. BMC Genomics 2016;17(Suppl 1):7. 108. Yeh YC, Wu CC, Wang YK, Tang MJ. DDR1 triggers epithelial cell differentiation by promoting cell adhesion through stabilization of E-cadherin. Mol Biol Cell 2011;22:950–953. 109. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, Briggs BB. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia 2007;9:166–180. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49530 | - |
dc.description.abstract | 論述重點:
臺灣食道癌之發生率與死亡率逐年上升,是國內男性前十大惡性腫瘤之一。多數病患因吞嚥困難而就醫確診,診斷時多已為局部晚期,因此預後不佳。此外百分之九十以上的病患罹患的食道癌組織類型為鱗狀上皮細胞癌,其與西方國家多為好發於中下段食道及胃食道交接處的腺癌,不論在致病機轉、危險因子、預後與治療反應等均有很大的不同。針對局部晚期食道癌,前瞻性隨機分派臨床研究顯示包含化學治療、放射治療以及根除性手術之治癒性整合治療能夠為病患帶來較佳的預後。儘管如此,病患整體的無病存活期中位數只達約 20 到 25 個月。同步化學放射治療不論是作為根除性手術前之前導性治療 或是治癒性治療,均能夠增加食道癌病患之整體存活率,因此同步化學放射治療已成為食道癌之標準方式治療之一。目前已知食道腫瘤能否在化學放射治療後達到病理完全緩解是重要的預後因子,但是目前臨床上仍然缺乏有效的方式來預測病患對於化學放射治療之反應與預後,從而從而擬定個人化的治療方式,以最大化治療效益並且最小化治療相關毒性。除此以外,食道鱗狀上皮細胞癌亦尚未有適當的標靶治療藥物能夠進一步增進治療反應率。因此我們試圖藉由微陣列晶片分析辨識與食道鱗狀上皮癌預後相關之創新生物標記並探討所發現生物標記之致癌機轉,藉由此轉譯醫學研究尋找具備預測與治療潛力的分子生物標靶,以期提升食道鱗狀上皮細胞癌之預後。 方法: 本研究分兩部分進行。第一部分收集食道鱗狀上皮細胞癌局部晚期病患於前導性同步化學放射治療前後周邊血液檢體,抽取其循環訊息核醣核酸(messenger RNA),進行微陣列晶片實驗取得表現體學資料,其後藉由生物資訊與生物統計方法辨識與病患接受根除性手術後達病理完全緩解最具關聯性的生物標記,並以反轉錄聚合酶鏈式反應來驗證發現結果,且在獨立病患群組中驗證其蛋白表現與預後之關聯性。同時我們亦在病理檢體與食道鱗狀上皮細胞癌細胞株偵測該創新生物標記是否過度表現,以證實其具有生物功能。第二部分,我們利用已建立的國人食道鱗狀上皮細胞癌細胞株,藉由調控該創新生物標記基因之表現量,探討該基因對細胞株在致癌能力與對化學放射治療反應之影響,並利用皮下異種腫瘤小鼠模式探討該基因在腫瘤生長與分化所扮演的角色。此外亦進行微陣列晶片實驗取得細胞株在有無抑制該基因之表現體學資料,尋找可能與該基因相關聯的基因。依據這些實驗,我們能夠更深入了解所辨識的創新生物標記在食道鱗狀上皮細胞癌所扮演的角色。 結果: 在第一部分研究方面,我們證實循環基因表現譜在化學放射治療前後會有顯著的變化,並且假設循環基因表現變化可用以預測治療結果。利用資訊學與統計學方法,我們成功辨識出一個食道鱗狀上皮細胞癌的創新生物標記,FAM84B。我們發現FAM84B此一循環訊息核醣核酸與蛋白在同步化學放射治療前後表現量的變化具有顯著的改變。該循環訊息核醣核酸表現量在前導性治療後下降的程度可以用來預測食道腫瘤對化學放射治療的反應程度。此外人類FAM84B蛋白在食道鱗狀上皮細胞癌病理切片與細胞株均呈現過度表現之現象,但在正常食道上皮組織與細胞則為低度表現。在第二部分研究方面,我們發現在食道癌細胞株將人類FAM84B蛋白表現以短髮夾核醣核酸干擾抑制後,其細胞之群落存活率與遷移能力均會下降。相反的,若細胞株過度表現FAM84B則會增加細胞株的群落存活率。而在小鼠異種移植腫瘤生長延遲實驗亦證實抑制FAM84B可以減少食道腫瘤的分裂與增殖能力,並且促使細胞分化較為良好。我們進一步研究發現,人類FAM84B對細胞致腫瘤性的機轉,可能與控制上皮細胞分化蛋白KRT15的表現有關。此外在細胞表現體學實驗分析部分,我們發現人類FAM84B會顯著降低細胞週期基因CCND2表現,並在細胞實驗證實抑制FAM84B會影響細胞週期在G1至S過渡期的進展。最後,我們也證實抑制人類FAM84B會影響食道鱗狀上皮癌細胞株對游離輻射與細胞毒殺藥物順鉑的存活率。 討論: 我們利用高通量生物標記檢測以及生物資訊學分析,發現了一個與食道鱗狀上皮細胞癌相關的周邊循環創新生物標記,人類FAM84B。值得注意的是,和其他類似研究不同,我們所發現的循環生物標記確實在食道鱗狀上皮細胞癌具有致癌特性。人類FAM84B基因位在第八對染色體長臂8q24.21的位置上。目前已知8q24.21該位置的拷貝數變異和許多癌症具有相關性,但由於其鄰近另一個重要的致癌基因,人類C-MYC,因此目前文獻上對於人類FAM84B在細胞功能與致癌機轉的瞭解仍相當的缺乏。我們的研究與其他學者的獨立研究,目前都證實了人類FAM84B在華裔食道鱗狀上皮細胞癌病患的致病機轉應該具有特定的角色。我們的實驗雖然證實人類FAM84B會影響食道癌細胞株的群落存活率、遷移能力、細胞週期、細胞分化與對去氧核醣核酸傷害之反應等,但在分子生物機轉細節方面,尚有待更深入的研究。而在我們的前期研究中更發現,人類FAM84B在食道鱗狀上皮細胞癌的主要病理變化可能是來自於拷貝數變異而非蛋白過度表現,並且在其他具有8q24.21拷貝數變異的惡性腫瘤,如大腸癌細胞株等證實抑制FAM84B能夠明顯降低細胞存活率。因此我們的研究發現僅是一個開端,值得後續的臨床檢體研究與實驗室基礎研究探索人類FAM84B在癌症生物學的功能。 | zh_TW |
dc.description.abstract | Background:
The incidence of esophageal cancer has increased year by year to become one of the ten most common and lethal cancers in Taiwanese males. Most patients are diagnosed with initial presentation of dysphagia and therefore have poor prognosis due to the locally advanced disease. Furthermore, the majority of patients have a histology of squamous cell carcinoma (SCC), which quite different in pathogenesis, risk factors, outcomes, and treatment responses, from the western countries, where adenocarcinoma of the lower esophagus and esophagogastric junction is predominant. For patients with locally advanced esophageal cancer, prospective randomized trials have shown that combined modality therapy, including chemotherapy, radiotherapy, and radical esophagectomy, provides the best treatment results. However, median progression free survival remains unsatisfactorily around 20 to 25 months. Concurrent chemoradiotherapy (CCRT), either as neoadjuvant or definitive therapy, improves the overall survival in patients with esophageal SCC (ESCC). It has been recognized that pathological complete response to CCRT is the most important prognostic factor. At present, there is no reliable factor which predicts response to chemoradiation, and thus enables the individualization of treatment strategies. Furthermore, there is no molecular target therapy to improve outcomes for ESCC. In the present study, we utilized microarray analysis to identify novel biomarkers in association with outcomes for ESCC and investigated underlying mechanisms in tumorigenicity. Our aim in conducting the present translational research was to discover biomarkers with the potential to predict outcomes and which may be used as therapeutic targets, to help improve the prognosis of ESCC. Methods: In the first part of this study, we collected blood samples in ESCC patients before and after neoadjuvant CCRT and extracted the messenger RNA. We performed microarray experiments and identified candidate circulating biomarkers using bioinformatics and biostatistics tools. We validated our findings using reverse-transcriptase polymerase chain reaction and proximal ligation assay to detect serum protein levels in an independent cohort. We also investigated whether the identified biomarker was overexpressed in cancerous tissues using immunohistochemistry (IHC) analysis, and in ESCC cell lines using western blot. In the second part, we used established ESCC cell lines to study the biological properties of the candidate gene by manipulating its expression levels. We performed in vitro cell assay and in vivo subcutaneous xenograft animal models. We also used a gene expression microarray analysis to identify candidate genes associated with our gene of interest. Results: In the first part, we showed that circulating expression profiles were significantly altered before and after CCRT. We therefore hypothesized that changes in gene expression may be associated with treatment outcome and successfully identified a novel candidate biomarker, human FAM84B. Expression levels of FAM84B were significantly down-regulated after CCRT and its fold change was predictive of pathological response to CCRT. Furthermore, we demonstrated that the human FAM84B protein was overexpressed in ESCC cancerous tissue and cell lines but not in the normal esophageal epithelium and epithelial cells. In the second part, we discovered that FAM84B knockdown by short hairpin RNA impaired the clonogenic survival and migration of ESCC cell lines, while FAM84B knock-in promoted clonogenic survival. Inhibition of FAM84B in ectopic xenografts also delayed tumor growth with reduced Ki-67 proliferation index, mitotic index, and promoted cell differentiation. We showed that the tumorigenicity of FAM84B may be associated with expression of the squamous cell differentiation protein KRT15. In addition, microarray analysis revealed that CCND2 expression was significantly associated with FAM84B expression. We demonstrated that inhibition of FAM84B delayed G1/S phase progression in the cell cycle by downregulating CCND2. In the last part, we showed that FAM84B was associated with sensitivity to ionizing radiation and cytotoxic cisplatin in ESCC cell lines. Discussion Unlike similar research, we identified a novel circulating biomarker with biological properties using high-throughput technology. Human FAM84B is located at chromosome 8q24.21, which is known to associate with different cancer types due to copy number alterations. The function of FAM84B is understudied due to its proximity to the well-known oncogene, MYC. However, we and other independent investigators have shown that FAM84B is associated with pathogenesis in ESCC in the Han population. While our earlier findings showed the oncogenic properties of FAM84B in ESCC, its molecular mechanisms required further investigation. In our preliminary research, we found that copy number variations in FAM84B may have a more important role in ESCC. Furthermore, inhibition of FAM84B in 8q24.21 amplified cancers, such as colorectal cancer cells, and significantly impaired cell proliferation. Our finding is only the beginning, and we believe it worth further investigation in both clinical specimens and laboratory work to study the role of FAM84B in cancer biology. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T11:33:13Z (GMT). No. of bitstreams: 1 ntu-105-D96945008-1.pdf: 4030139 bytes, checksum: ce459d030f1a69f8ffa91c9b0c8120cb (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT v CONTENTS viii LIST OF TABLES xii LIST OF FIGURES xiii Chapter 1 Introduction 1 1.1 Esophageal Squamous Cell Carcinoma 1 1.2 Prognostic Factors of Esophageal Cancer Undergoing Chemoradiation 2 1.3 Predictors of Pathological Response to Concurrent Chemoradiation for Esophageal Cancer 3 1.4 Genetic Alterations and Target Therapies in Esophageal Squamous Cell Carcinoma 4 1.5 Rationale of Present Doctoral Dissertation 5 Chapter 2 Part I: Circulating Expression Profiles in Identifying Novel Biomarkers Predicting Pathological Response to Neuadjuvant Chemoradiation for Esophageal Squamous Cell Carcinoma 6 2.1 Background 6 2.1.1 Microarray Analysis in Identifying Predictive Biomarkers 6 2.1.2 Circulating Predictive Biomarkers 7 2.2 Materials and Methods 9 2.2.1 Study Design 9 2.2.2 Patients 9 2.2.3 Treatment 9 2.2.4 Outcome Measurement 10 2.2.5 Sample Collection 10 2.2.6 RNA Extraction 11 2.2.7 Microarray Experiment 11 2.2.8 Quantitative Reverse Transcription Polymerase Chain Reaction 12 2.2.9 Proximal Ligation Assay 13 2.2.10 Enzyme-Linked Immunosorbent Assay 14 2.2.11 Immunohistochemistry Analysis 15 2.2.12 Western Blot 15 2.2.13 Bioinformatics Analysis 16 2.2.14 Statistically Analysis 17 2.3 Results 18 2.3.1 Patient Characteristics 18 2.3.2 CCRT Alters Circulating Expression Profiles 18 2.3.3 Change in Circulating Expression Profiles Differ Between Pathological Complete Responders and Non-Complete Responders 20 2.3.4 Circulating FAM84B mRNA Expression as A Novel Biomarker 21 2.3.5 Serum FAM84B Protein Levels in Association with CCRT Response 21 2.3.6 FAM84B Overexpression in Tumor Tissue 22 2.3.7 FAM84B Overexpression in Esophageal Squamous Cell Carcinoma Cell Lines 23 2.4 Discussion 24 Chapter 3 Part II: Investigation the Oncological Properties of FAM84B in Tumorigenesis of Esophageal Squamous Cell Carcinoma Cell Lines 27 3.1 Background 27 3.1.1 FAM84B in Tumorigenesis 27 3.1.2 The Function of FAM84B 28 3.2 Materials and Methods 30 3.2.1 Cell Lines and Culture 30 3.2.2 FAM84B Knockdown 30 3.2.3 Overexpressing FAM84B 31 3.2.4 Clonogenic Survival Assay 31 3.2.5 Quantitative Reverse Transcription Polymerase Chain Reaction 32 3.2.6 Western Blot 33 3.2.7 Cell Migration Assay 34 3.2.8 Immunofluorescence Microscopy 35 3.2.9 Microarray Analysis 35 3.2.10 Cell Cycle Analysis 36 3.2.11 Tumor Growth Delay Assay 36 3.2.12 Histological Evaluation 37 3.2.13 Statistical Analysis 38 3.3 Results 39 3.3.1 FAM84B is Not Co-expressed with c-MYC 39 3.3.2 FAM84B is Associated with Cell Clonogenicity 39 3.3.3 FAM84B Inhibition Attenuates Cell Migration 40 3.3.4 FAM84B Inhibition Suppresses Ectopic Tumor Growth 41 3.3.5 FAM84B and Cell Differentiation 42 3.3.6 Differentially Expressed Genes Associated with FAM84B 43 3.3.7 FAM84B Depletion Affects G1/S Progression 43 3.3.8 FAM84B Knockdown Increases Sensitivity to Chemoradiation 44 3.4 Discussion 45 Chapter 4 Perspectives 49 4.1 Limitations 49 4.2 Future Directions 50 4.3 Conclusion 51 TABLES 53 FIGURES 63 REFERENCE 91 | |
dc.language.iso | en | |
dc.title | 利用微陣列晶片分析辨識與食道鱗狀上皮癌預後相關之創新生物標記並探討其分子生物機轉之轉譯醫學研究 | zh_TW |
dc.title | Identification of A Novel Biomarker Using Microarray Analysis and Investigation of Its Molecular Mechanisms in Esophageal Squamous Cell Carcinoma: A Translational Cancer Study | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 成佳憲(Jason Chia-Hsien Cheng),黃正仲(Jeng-Jong Hwang),歐陽彥正(Yen-Jen Oyang),李章銘(Jang-Ming Lee),徐中平(Chung-Ping Hsu) | |
dc.subject.keyword | 人類FAM84B,生物標記,同步化學放射治療,食道鱗狀細胞癌,基因靶向,致腫瘤性,微陣列晶片分析, | zh_TW |
dc.subject.keyword | Biomarkers,Carcinogenesis,Concurrent chemoradiotherapy,Esophageal squamous cell carcinoma,Gene targeting,Human FAM84B,Microarray analysis, | en |
dc.relation.page | 105 | |
dc.identifier.doi | 10.6342/NTU201602635 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2016-08-17 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
顯示於系所單位: | 生醫電子與資訊學研究所 |
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