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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 俞松良(Sung-Liang Yu) | |
dc.contributor.advisor | 俞松良(Sung-Liang Yu | slyu@ntu.edu.tw | ), | |
dc.contributor.author | Chen-Wei Hsu | en |
dc.contributor.author | 徐臣緯 | zh_TW |
dc.date.accessioned | 2023-03-19T22:08:23Z | - |
dc.date.copyright | 2022-06-21 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-06-06 | |
dc.identifier.citation | 1. Siegel, R.L., et al., Cancer statistics, 2022. CA: a cancer journal for clinicians, 2022. 2. Ferlay, J., et al., Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer, 2015. 136(5): p. E359-86. 3. Hirsch, F.R. and P.A. Bunn, Jr., EGFR testing in lung cancer is ready for prime time. Lancet Oncol, 2009. 10(5): p. 432-3. 4. Langer, C.J., Epidermal growth factor receptor inhibition in mutation-positive non-small-cell lung cancer: is afatinib better or simply newer? J Clin Oncol, 2013. 31(27): p. 3303-6. 5. O'Kane, G.M., et al., Uncommon EGFR mutations in advanced non-small cell lung cancer. Lung Cancer, 2017. 109: p. 137-144. 6. Riely, G.J., et al., Update on epidermal growth factor receptor mutations in non-small cell lung cancer. Clin Cancer Res, 2006. 12(24): p. 7232-41. 7. Robichaux, J.P., et al., Mechanisms and clinical activity of an EGFR and HER2 exon 20-selective kinase inhibitor in non-small cell lung cancer. Nat Med, 2018. 8. Howlader N, N.A., Krapcho M, et al. . SEER Cancer Stastics Review, 1975-2014, based on Novenber 2016 SEER data submission, posted to the SEER web site, April 2017. Bethesda, MD: National Cancer Institute. 2017. 9. Lindeman, N.I., et al., Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J Thorac Oncol, 2013. 8(7): p. 823-59. 10. Ferrara, R., et al., Clinical and Translational Implications of RET Rearrangements in Non-Small Cell Lung Cancer. J Thorac Oncol, 2018. 13(1): p. 27-45. 11. Ferrara, R., L. Mezquita, and B. Besse, Progress in the Management of Advanced Thoracic Malignancies in 2017. J Thorac Oncol, 2018. 13(3): p. 301-322. 12. Forde, P.M., et al., Neoadjuvant PD-1 Blockade in Resectable Lung Cancer. N Engl J Med, 2018. 13. Reck, M., et al., Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer. N Engl J Med, 2016. 375(19): p. 1823-1833. 14. Gandhi, L., et al., Pembrolizumab plus Chemotherapy in Metastatic Non-Small-Cell Lung Cancer. N Engl J Med, 2018. 15. Carbone, D.P., et al., First-Line Nivolumab in Stage IV or Recurrent Non-Small-Cell Lung Cancer. N Engl J Med, 2017. 376(25): p. 2415-2426. 16. Hellmann, M.D., et al., Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N Engl J Med, 2018. 17. Rittmeyer, A., et al., Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet, 2017. 389(10066): p. 255-265. 18. Doroshow, D.B. and R.S. Herbst, Treatment of Advanced Non-Small Cell Lung Cancer in 2018. JAMA Oncol, 2018. 4(4): p. 569-570. 19. Wei, L., et al., Circulating tumor DNA measurement provides reliable mutation detection in mice with human lung cancer xenografts. Lab Invest, 2018. 20. Bettegowda, C., et al., Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med, 2014. 6(224): p. 224ra24. 21. Phallen, J., et al., Direct detection of early-stage cancers using circulating tumor DNA. Sci Transl Med, 2017. 9(403). 22. Zhu, Y.J., et al., Quantitative cell-free circulating EGFR mutation concentration is correlated with tumor burden in advanced NSCLC patients. Lung Cancer, 2017. 109: p. 124-127. 23. Siravegna, G., et al., Integrating liquid biopsies into the management of cancer. Nat Rev Clin Oncol, 2017. 14(9): p. 531-548. 24. Alix-Panabieres, C. and K. Pantel, Clinical Applications of Circulating Tumor Cells and Circulating Tumor DNA as Liquid Biopsy. Cancer Discov, 2016. 6(5): p. 479-91. 25. Ilie, M., et al., 'Sentinel' circulating tumor cells allow early diagnosis of lung cancer in patients with chronic obstructive pulmonary disease. PLoS One, 2014. 9(10): p. e111597. 26. Cohen, J.D., et al., Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science, 2018. 359(6378): p. 926-930. 27. Krebs, M.G., et al., Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer. J Clin Oncol, 2011. 29(12): p. 1556-63. 28. Bidard, F.C., et al., Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data. Lancet Oncol, 2014. 15(4): p. 406-14. 29. Cohen, S.J., et al., Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. J Clin Oncol, 2008. 26(19): p. 3213-21. 30. Hou, J.M., et al., Clinical significance and molecular characteristics of circulating tumor cells and circulating tumor microemboli in patients with small-cell lung cancer. J Clin Oncol, 2012. 30(5): p. 525-32. 31. Scher, H.I., et al., Circulating tumor cell biomarker panel as an individual-level surrogate for survival in metastatic castration-resistant prostate cancer. J Clin Oncol, 2015. 33(12): p. 1348-55. 32. Douillard, J.Y., et al., First-line gefitinib in Caucasian EGFR mutation-positive NSCLC patients: a phase-IV, open-label, single-arm study. Br J Cancer, 2014. 110(1): p. 55-62. 33. Merker, J.D., et al., Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. J Clin Oncol, 2018: p. JCO2017768671. 34. Cho, H., et al., Microfluidic technologies for circulating tumor cell isolation. Analyst, 2018. 143(13): p. 2936-2970. 35. Pantel, K., R.H. Brakenhoff, and B. Brandt, Detection, clinical relevance and specific biological properties of disseminating tumour cells. Nat Rev Cancer, 2008. 8(5): p. 329-40. 36. Bidard, F.C., et al., Clinical application of circulating tumor cells in breast cancer: overview of the current interventional trials. Cancer Metastasis Rev, 2013. 32(1-2): p. 179-88. 37. Pantel, K. and C. Alix-Panabieres, Real-time liquid biopsy in cancer patients: fact or fiction? Cancer Res, 2013. 73(21): p. 6384-8. 38. Ashworth, T.R., A case of cancer in which cells similar to those in the tumors were seen in the blood after death. Medical Journal, 1869. 14: p. 146-149. 39. Moreno, J.G., et al., Changes in circulating carcinoma cells in patients with metastatic prostate cancer correlate with disease status. Urology, 2001. 58(3): p. 386-92. 40. Kim, M.Y., et al., Tumor self-seeding by circulating cancer cells. Cell, 2009. 139(7): p. 1315-26. 41. Valastyan, S. and R.A. Weinberg, Tumor metastasis: molecular insights and evolving paradigms. Cell, 2011. 147(2): p. 275-92. 42. Fluegen, G., et al., Phenotypic heterogeneity of disseminated tumour cells is preset by primary tumour hypoxic microenvironments. Nat Cell Biol, 2017. 19(2): p. 120-132. 43. Abbosh, C., et al., Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature, 2017. 545(7655): p. 446-451. 44. de Sousa, V.M.L. and L. Carvalho, Heterogeneity in lung cancer. Pathobiology, 2018. 85(1-2): p. 96-107. 45. Jia, Q., et al., Local mutational diversity drives intratumoral immune heterogeneity in non-small cell lung cancer. Nature communications, 2018. 9(1): p. 1-10. 46. Freitas, C., et al., The role of liquid biopsy in early diagnosis of lung cancer. Frontiers in Oncology, 2021. 11: p. 1130. 47. Pisapia, P., et al., Next generation sequencing for liquid biopsy based testing in non-small cell lung cancer in 2021. Critical Reviews in Oncology/Hematology, 2021. 161: p. 103311. 48. Salvianti, F., et al., Circulating tumour cells and cell-free DNA as a prognostic factor in metastatic colorectal cancer: The OMITERC prospective study. British Journal of Cancer, 2021. 125(1): p. 94-100. 49. Tombolan, L., et al., Clinical significance of circulating tumor cells and cell‐free DNA in pediatric rhabdomyosarcoma. Molecular Oncology, 2022. 50. Schwarzenbach, H., D.S. Hoon, and K. Pantel, Cell-free nucleic acids as biomarkers in cancer patients. Nature Reviews Cancer, 2011. 11(6): p. 426-437. 51. Thress, K.S., et al., EGFR mutation detection in ctDNA from NSCLC patient plasma: a cross-platform comparison of leading technologies to support the clinical development of AZD9291. Lung cancer, 2015. 90(3): p. 509-515. 52. Francis, G. and S. Stein, Circulating cell-free tumour DNA in the management of cancer. International journal of molecular sciences, 2015. 16(6): p. 14122-14142. 53. Scharpenseel, H., et al., EGFR and HER3 expression in circulating tumor cells and tumor tissue from non-small cell lung cancer patients. Scientific reports, 2019. 9(1): p. 1-9. 54. Tellez-Gabriel, M., M.-F. Heymann, and D. Heymann, Circulating tumor cells as a tool for assessing tumor heterogeneity. Theranostics, 2019. 9(16): p. 4580. 55. Vasseur, A., et al., Clinical utility of circulating tumor cells: An update. Molecular oncology, 2021. 15(6): p. 1647-1666. 56. Giuliano, M., et al., Circulating tumor cells as prognostic and predictive markers in metastatic breast cancer patients receiving first-line systemic treatment. Breast Cancer Res, 2011. 13(3): p. R67. 57. Toss, A., et al., CTC enumeration and characterization: moving toward personalized medicine. Annals of Translational Medicine, 2014. 2(11): p. 108. 58. Hong, B. and Y. Zu, Detecting circulating tumor cells: current challenges and new trends. Theranostics, 2013. 3(6): p. 377-94. 59. Hanssen, A., et al., Detection of Circulating Tumor Cells in Non-Small Cell Lung Cancer. Frontiers in Oncology, 2015. 5: p. 207. 60. Navin, N.E., The first five years of single-cell cancer genomics and beyond. Genome Res, 2015. 25(10): p. 1499-507. 61. Alva, A., et al., Circulating Tumor Cells as Potential Biomarkers in Bladder Cancer. The Journal of Urology, 2015. 194(3): p. 790-798. 62. Polzer, B., et al., Molecular profiling of single circulating tumor cells with diagnostic intention. EMBO Molecular Medicine, 2014. 63. Pestrin, M., et al., Heterogeneity of PIK3CA mutational status at the single cell level in circulating tumor cells from metastatic breast cancer patients. Molecular Oncology, 2015. 9(4): p. 749-757. 64. Gebreyesus, S.T., et al., Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry. Nature communications, 2022. 13(1): p. 1-13. 65. Leblanc, R. and O. Peyruchaud, Metastasis: new functional implications of platelets and megakaryocytes. Blood, 2016. 128(1): p. 24-31. 66. Labelle, M., S. Begum, and R.O. Hynes, Direct signaling between platelets and cancer cells induces an epithelial-mesenchymal-like transition and promotes metastasis. Cancer Cell, 2011. 20(5): p. 576-90. 67. Giorgi, U.D., Correlation of circulating tumor cells (CTCs) with peripheral blood leukocytes to predict outcome in metastatic breast cancer (MBC). J Clin Oncol, 2016. 68. Chua, W., et al., Neutrophil/lymphocyte ratio predicts chemotherapy outcomes in patients with advanced colorectal cancer. Br J Cancer, 2011. 104(8): p. 1288-95. 69. Guthrie, G.J., et al., The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol, 2013. 88(1): p. 218-30. 70. Kao, S.C., et al., High blood neutrophil-to-lymphocyte ratio is an indicator of poor prognosis in malignant mesothelioma patients undergoing systemic therapy. Clin Cancer Res, 2010. 16(23): p. 5805-13. 71. Templeton, A.J., et al., Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst, 2014. 106(6): p. dju124. 72. Yao, Y., et al., Pretreatment neutrophil to lymphocyte ratio is associated with response to therapy and prognosis of advanced non-small cell lung cancer patients treated with first-line platinum-based chemotherapy. Cancer Immunol Immunother, 2013. 62(3): p. 471-9. 73. Punnoose, E.A., et al., Evaluation of circulating tumor cells and circulating tumor DNA in non-small cell lung cancer: association with clinical endpoints in a phase II clinical trial of pertuzumab and erlotinib. Clin Cancer Res, 2012. 18(8): p. 2391-401. 74. Remon, J., et al., The APPLE Trial: Feasibility and Activity of AZD9291 (Osimertinib) Treatment on Positive PLasma T790M in EGFR-mutant NSCLC Patients. EORTC 1613. Clin Lung Cancer, 2017. 18(5): p. 583-588. 75. Labib, M. and S.O. Kelley, Circulating tumor cell profiling for precision oncology. Molecular oncology, 2021. 15(6): p. 1622-1646. 76. Bhat, M.P., et al., Recent Advances in Microfluidic Platform for Physical and Immunological Detection and Capture of Circulating Tumor Cells. Biosensors, 2022. 12(4): p. 220. 77. Gao, W., et al., EGFR point mutation detection of single circulating tumor cells for lung cancer using a micro-well array. Biosens Bioelectron, 2019. 139: p. 111326. 78. Polzer, B., et al., Molecular profiling of single circulating tumor cells with diagnostic intention. EMBO molecular medicine, 2014. 6(11): p. 1371-1386. 79. Krebs, M.G., et al., Molecular analysis of circulating tumour cells—biology and biomarkers. Nature reviews Clinical oncology, 2014. 11(3): p. 129-144. 80. Ozkumur, E., et al., Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells. Sci Transl Med, 2013. 5(179): p. 179ra47. 81. Nadal, R., et al., CD133 expression in circulating tumor cells from breast cancer patients: potential role in resistance to chemotherapy. Int J Cancer, 2013. 133(10): p. 2398-407. 82. Kasimir-Bauer, S., et al., Expression of stem cell and epithelial-mesenchymal transition markers in primary breast cancer patients with circulating tumor cells. Breast Cancer Research, 2012. 14(1): p. 1-9. 83. Musella, V., et al., Circulating tumor cells as a longitudinal biomarker in patients with advanced chemorefractory, RAS‐BRAF wild‐type colorectal cancer receiving cetuximab or panitumumab. International Journal of Cancer, 2015. 137(6): p. 1467-1474. 84. Heller, G., et al., Circulating tumor cell number as a response measure of prolonged survival for metastatic castration-resistant prostate cancer: a comparison with prostate-specific antigen across five randomized phase III clinical trials. Journal of Clinical Oncology, 2018. 36(6): p. 572. 85. Tarhan, M.O., et al., Prognostic significance of circulating tumor cells and serum CA15-3 levels in metastatic breast cancer, single center experience, preliminary results. Asian Pacific Journal of Cancer Prevention, 2013. 14(3): p. 1725-1729. 86. Cohen, E.N., et al., Enumeration and molecular characterization of circulating tumor cells enriched by microcavity array from stage III non-small cell lung cancer patients. Transl Lung Cancer Res, 2020. 9(5): p. 1974-1985. 87. Lim, M., et al., A lab-on-a-disc platform enables serial monitoring of individual CTCs associated with tumor progression during EGFR-targeted therapy for patients with NSCLC. Theranostics, 2020. 10(12): p. 5181. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84315 | - |
dc.description.abstract | 肺癌是全球癌症相關死亡的主要原因,其抗藥性和癌細胞轉移時常發生在晚期非小細胞肺癌(NSCLC)。非侵入性液態活檢包括循環腫瘤細胞(CTC)在內,提供了另一種方法用以監測疾病進展與檢測用藥基因突變。因此我們建立了一個可以同時有效進行臨床監控和基因檢測的高純度細胞分離系統。此分離系統是基於免疫抗體磁珠(immunomagnetic bead)來完成CTC富集並透過介電泳(dielectrophoretic)分離系統達到單細胞純化。下一步利用質譜儀(MASS)和次世代定序(NGS)分析測得循環腫瘤細胞的基因突變。首先,我們通過客製化的上皮細胞粘附分子(EpCAM)抗體優化了免疫抗體磁珠的富集效率,並使用外加H1975細胞株於全血的方式來評估目標細胞的回收率和純度,接著進一步評估基因檢測需要的最小細胞數極限,也在晚期非小細胞肺癌患者中觀察到了CTC數量的動態變化。在體外測試結果中免疫抗體磁珠富集系統裡客製化的EpCAM抗體能將富集回收率從70%提高到88%。最後純化成功的單細胞全基因擴增成功率為60%,質譜儀檢測單細胞表皮生長因子接受器(EGFR) L858R和T790M基因突變的一致性為100%,變異係數(CV)分別為4%和5%。在NGS中,純化後的H1975細胞株一顆細胞、五顆細胞和十顆細胞的十倍深度覆蓋率(coverage)分別為59.92%、61.68%和79.27%。臨床測試結果中從NSCLC患者周邊血分離的 10 顆CTC裡鑑定出了EGFR del 19基因突變。我們也同時觀察到了CTC計數與其他臨床治療的臨床相關性,發現中性粒細胞與淋巴細胞的比率(NLR)與CTC計數結合可能能作為預後不良的潛在指標。值得注意的是,CTC數量的動態變化有潛力可以預測多發性腦轉移和肺到肺轉移。另外我們還發現了結合CTC和循環游離核酸(cfDNA)的NGS分析結果可以提高基因檢測的檢測率。綜合以上,我們建立了基於免疫抗體磁珠介電泳的方法來純化高純度CTC,且可同時監測CTC數量和基因突變,並展現CTC有潛力在肺癌病患預測與預後中可以當作生物標誌物用於測量癌症主導基因(driver gene)的表現,顯示了CTC應用於肺癌患者個人化治療的可行性。 | zh_TW |
dc.description.abstract | Lung cancer is the leading cause of cancer-related deaths worldwide. The drug resistance and metastasis eventually occurred in advanced non-small cell lung cancer (NSCLC). Non-invasive liquid biopsy including circulating tumor cell (CTC) provides an alternative solution to monitor disease progress and identify druggable mutations once progressive disease occurred. We establish an effective system for high-purity CTC isolation for monitoring and gene testing simultaneously. An immunomagnetic bead-based enrichment system was used for CTC enrichment and a dielectrophoretic separation system was used for single cell sorting. Gene mutations of resulting CTCs were analyzed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and next-generation sequencing (NGS). First, we optimized the efficiency of immunomagnetic beads-based CTC enrichment by customized EpCAM antibodies and spiked H1975 cells were used for the evaluation of recovery rate and purity. The minimal number of CTCs for gene testing was evaluated and the dynamic change of CTC number was determined in advanced NSCLC. The customized EpCAM pooled antibodies improved the recovery rates of immunomagnetic beads-based enrichment system from 70% to 88% in three spiked cell lines. The successful rate of single cell whole genome amplification is 60% and the concordance of both L858R and T790M EGFR mutations in a single cell assayed by MALDI-TOP MS is 100% and coefficient variations are 4% and 5%, respectively. The coverages of 10X depth of NGS in 1-cell, 5-cell and 10-cell groups of H1975 cells are 59.92%, 61.68% and 79.27%, respectively. EGFR del 19 mutation was identified in 10 CTCs isolated from NSCLC patients. We demonstrated the clinical correlation of CTC count with other clinical treatment and peripheral blood cells, neutrophil-to-lymphocyte ratio (NLR), might serve as a potential indicator of poor prognosis Notably, the dynamic changes of CTC number may predict multiple brain and lung-to-lung metastases. We also found that combining CTC and circulating cell free DNA (cfDNA) may improve the detection rate on the NGS result of gene detection. Taken together, We established the magnetic beads-based dielectrophoretic sorting method for high-purity CTC capture which can enumerate CTC number and determine gene mutations simultaneously and evaluate the feasibility of serial CTC detections and gene testing for personalized therapy of lung cancer patients, evaluate the driver gene expression for predictive and prognostic biomarkers in lung cancer patients. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T22:08:23Z (GMT). No. of bitstreams: 1 U0001-1705202211160200.pdf: 5647459 bytes, checksum: 332408b34c8a4e4a0265f8aa698887bf (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 口試委員會審定書 i 致謝 ii 中文摘要 iii Abstract v 1. Introduction 1 1.1 Lung Cancer 2 1.2 Liquid biopsy 3 1.3 Circulating tumor cells 4 1.4 The correlation between CTCs with other cells in bloodstream 7 1.5 Ongoing CTC clinical applications 8 1.6 Specific aims 9 2. Materials and Methods 11 2.1 Cell lines 12 2.2 Patients 12 2.3 Blood spiking experiment and sample processing 13 2.4 Flow cytometry 14 2.5 High-content imaging 14 2.6 Dielectrophoretic Sorting 15 2.7 EGFR mutation analysis by MALDI-TOF MS 16 2.8 Whole genome amplification 16 2.9 Next-generation sequencing 16 2.10 Statistical analysis 17 3. Results 18 3.1 Optimization of EpCAM-based CTC capture efficiency 19 3.2 Single cell isolation by DEPArray 20 3.3 The application of actionable mutation detection for the magnetic beads-based dielectrophoretic isolation platform 21 3.4 CTCs purified by the magnetic beads-based dielectrophoretic isolation system capable for gene testing clinically 22 3.5 Longitudinal monitoring disease progression and CTC counting 23 3.6 Optimization of NGS result from different quality CTC 25 3.7 Clinical correlation between CTC and other peripheral blood cells 25 3.8 Combining CTC counts and NLR as an indicator of prognosis 27 3.9 Dynamic change of CTC numbers after the first treatment 29 3.10 Comparing dynamic CTC numbers change among brain metastasis 31 3.11 Improve the detection rate by combining NGS result of CTC and cfDNA 31 4. Discussion 33 5. Figures 37 Figure 1. The magnetic beads-based dielectrophoretic isolation platform. 38 Figure 2. Performance assessment of optimized IsoFlux CTC enrichment. 40 Figure 3. Single cell identified and sorted by DEPArray. 43 Figure 4. The gene testing of the magnetic beads-based dielectrophoretic isolation platform-sorted single cell. 45 Figure 5. The driver mutation detection of CTCs from advance NSCLC patients. 47 Figure 6. Dynamic change of CTCs counts across EGFR-TKI treatment. 48 Figure 7. The collection profile of NSCLC patients. 50 Figure 8. The NGS result of the different quality circulating tumor cells. 51 Figure 9. Clinical correlation of CTC count with other peripheral blood cells. 52 Figure 10. Correlation between CTCs and monocytes in different EGFR mutations. 54 Figure 11. The comparison of NLR between NSCLC patients with different prognosis. 55 Figure 12. Optimization of overall survival curve from CTC counts and NLR value. 57 Figure 13. The overall survival curve result of combining CTC counts and NLR value. 58 Figure 14. CTC count slightly decreased after the first standard chemotherapy. 59 Figure 15. CTC count dynamically changed after different TKIs treatment in EGFR mutations patients. 60 Figure 16. The dynamic CTC numbers change before brain metastasis. 62 Figure 17. The comparison testing schematic of the CTC and cfDNA 63 Figure 18. Different condition result of the mutation profiles between CTC cell pellet and cfDNA. 64 Figure 19. Comparison of the mutation profiles combining CTC cell pellet and cfDNA. 65 6. Tables 66 Table 1. EGFR mutation frequency detected by MALDI-TOF MS in H1975 single clones. 67 Table 2. Reproducibility of one CTC gene testing by the magnetic beads-based dielectrophoretic isolation and MALDI-TOF MS. 68 Table 3. The performance comparison of Comprehensive Cancer Panel for 1,5, and 10 cells of H1975. 69 Table 4. The EGFR mutation frequency of patient-purified CTCs determined by MALDI-TOF MS. 70 Table 5. The quality control result in different single tumor cells from clinical patient. 71 Table 6. The NGS result of the different quality circulating tumor cells. 72 Table 7. The overall survival curve result of combining CTC counts and NLR value. 73 Table 8. The variant calling numbers of the mutation profiles from CTC cell pellet and cfDNA. 74 Table 9. The mutation variant calling result of the CTC cell pellet and cfDNA. 75 References 76 | |
dc.language.iso | en | |
dc.title | 基於循環腫瘤細胞的應用於晚期非小細胞肺癌患者其預後和基因檢測 | zh_TW |
dc.title | The Circulating Tumor Cell-based Application for Prognosis and Genetic Testing in Advanced Non-small Cell Lung Cancer Patients | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 何肇基(Chao-chi Ho),蘇剛毅(Kang-Yi Su),李明學(Ming-Shyue Lee),華國泰(Kuo-Tai Hua) | |
dc.subject.keyword | 循環腫瘤細胞,CTC,細胞分離,肺癌,NGS,動態變化, | zh_TW |
dc.subject.keyword | circulating tumor cell,CTC,cell isolation,lung cancer,NGS,dynamic change, | en |
dc.relation.page | 89 | |
dc.identifier.doi | 10.6342/NTU202200771 | |
dc.rights.note | 同意授權(限校園內公開) | |
dc.date.accepted | 2022-06-07 | |
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 |
dc.date.embargo-lift | 2022-06-21 | - |
顯示於系所單位: | 醫學檢驗暨生物技術學系 |
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