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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.author | Yuan-Chi Chou | en |
dc.contributor.author | 周源祈 | zh_TW |
dc.date.accessioned | 2021-06-17T03:13:24Z | - |
dc.date.available | 2023-08-01 | |
dc.date.copyright | 2018-08-01 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-07-12 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69345 | - |
dc.description.abstract | 過去十年,關於表皮生長因子受體(EGFR)突變的研究以及標靶治療藥物的研發造就了現今精準醫療在晚期非小細胞肺癌(NSCLC)領域的盛行發展。有鑑於晚期非小細胞肺癌病患不易進行手術切除或是穿刺來取得組織檢體,因此非侵入性液態檢體像是循環腫瘤細胞(CTC)及循環腫瘤去氧核醣核酸(ctDNA)開啟了另一扇門以更少的風險來取得病人的基因資訊以及用來預測或是監測治療效果。在液態檢體領域中,從數十億的血液細胞分離出高純度循環腫瘤細胞是相當困難但必須面對的挑戰,因此我們建立了一套結合IsoFlux和高內涵顯微影像分析系統(High-content imaging)兩個平台的縝密流程,用來計數富集出來的循環腫瘤細胞。到目前為止,我們已完成89名晚期非小細胞肺癌病患的收案,其中包含62名帶有EGFR突變,另外27名則是EGFR正常的病患,收案流程為追蹤每名病人在第一次用藥治療前到產生疾病進展(Progressive Disease, PD),期間每三個月將對病患抽7.5毫升的全血來進行接下來的循環腫瘤細胞計數,從IsoFlux富集後的腫瘤細胞將會進行染色並在高內涵顯微影像分析系統中辨認循環腫瘤細胞(Hoechst 33342+/Pan-CK+/CD45-),計數細胞後並計算循環腫瘤細胞的純度。除此之外,我們共同比較了其他臨床檢驗上重要的血球細胞與同在周邊血液中循環腫瘤細胞的交互關聯性,並發現血球細胞像是血小板、單核球以及嗜中性球的數量似乎與循環腫瘤細胞數呈現正相關;而另一個可經計算得到並與全身性發炎相關的指標neutrophil-to-lymphocyte ratio (NLR)也被觀察到有較高的數值在預後較差的病患,尤其是EGFR正常的病人。值得注意的是,此類型的縱向研究(longitudinal study)其實是一種液態檢體即時監控的概念(Real-time monitoring),其中包含了CTC數量的動態變化以及隨著治療療程的基因變異,本篇研究會專注在CTC數量在療程中的動態變化,分為第一次治療以及產生疾病進展兩個重要時間點來討論。在給予化療藥物的組別中,67% EGFR正常的病患(n=9)在治療後CTC數量有下降的趨勢;但在服用酪氨酸激酶抑制劑(EGFR-TKI)的EGFR突變病人中(n=28),57%晚期非小細胞肺癌病患(n=16)反而是有CTC數量上升的趨勢,尤以Afatinib治療後最明顯。我們也蒐集了所有病人的各時間點CTC數量依據病程發展做數量上的比較,可以發現當病患在12個月內發生PD,也就是在預後最差的組別中有最高的CTC數量。最後,我們選擇四名病患來全面追蹤治療過程中的疾病變化和用藥反應與CTC的動態變化並畫出縱向研究的時間與CTC數量進程圖。總結,CTC和NLR有潛力發展成共伴的合併生物標記,並在臨床上用來監測治療以及評估預後,而這需要有更多的試驗病人來做更深入的臨床應用之確認。 | zh_TW |
dc.description.abstract | In the last decade, the studies of epidermal growth factor receptor (EGFR) mutations and the development of targeted therapies have launched the new era of precision medicine in advanced non-small-cell lung cancer (NSCLC). Non-invasive liquid biopsies including circulating tumor cell (CTC) and circulating tumor DNA (ctDNA) initiate an alternative way to monitor treatment outcomes and to obtain tumor mutant genomic profiles. However, isolating high-purity CTCs from billions of blood cells is regarded as a challenging task but essential for studies in the liquid biopsy field; therefore, we set up a robust workflow combined IsoFlux and high-content imaging platforms to enumerate CTCs. Up to now, we have recruited 89 advanced NSCLC patients including 62 mutant EGFR and 27 wild-type EGFR cases. We collected 7.5 ml whole blood in EDTA tube for CTC enumeration from every treatment-naïve patient every three months until progressive disease (PD) occurred. After the enrichment of CTCs from the IsoFlux system, we applied the high content imaging platform to identify CTCs (Hoechst 33342+/Pan-CK+/CD45-) for enumeration and calculating CTCs purity. Furthermore, we demonstrated the clinical correlation of CTC count with other peripheral blood cells and suggested that blood cell types such as platelets, monocytes and neutrophils might positively correlated with CTCs in the peripheral blood. Another ready available index, neutrophil-to-lymphocyte ratio (NLR) might serve as a potential indicator of poor prognosis, especially in EGFR wild type patients. Notably, this kind of longitudinal study connoted the meaning of real-time monitoring, and we focused on the CTC count dynamic change at the time points of the first treatment and PD. Among patients initially treated with chemotherapy, CTC count decreased in 67% EGFR wild type patients (n=9); however, in the case of EGFR mutations patients (n=28) treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs), the increase of CTC count was found in 57% patients (n=16), especially after the Afatinib therapy. Taken together, high CTC count was observed in the patients with worse outcome and the confirmed disease progression was occurred within 12 months since the first treatment. Lastly, we chose four patients for longitudinal case discussion along with entire disease courses. In conclusion, the combination of CTC count and NLR may serve as the potential prognostic biomarkers in clinical practice but still needs a larger cohort for further investigation. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T03:13:24Z (GMT). No. of bitstreams: 1 ntu-107-R05424019-1.pdf: 3121094 bytes, checksum: 7c1a166a36924e0b92ec1e7a89c11ece (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 口試委員審定書 I
致謝 II 中文摘要 III Abstract V 1. Introduction 1 1.1 Lung cancer 2 1.1.1 Histology 3 1.1.2 EGFR Mutations 4 1.1.3 Advanced-stage NSCLC 4 1.2 Tyrosine Kinase Inhibitor (TKI) 5 1.2.1 Gefitinib 6 1.2.2 Erlotinib 6 1.2.3 Afatinib 7 1.2.4 Osimertinib 7 1.3 Liquid Biopsy 8 1.4 Circulating Tumor Cells (CTCs) 9 1.4.1 Epithelial Cell Adhesion Molecule (EpCAM) 10 1.4.2 Isolation 10 1.4.3 Circulating Tumor Microemboli (CTM) 11 1.4.4 Metastasis in CTCs Perspective 12 1.4.5 Interaction between CTCs with Other Cells in Bloodstream 13 1.4.6 Clinical Applications and Trials 14 1.5 Specific Aims 15 2. Materials and Methods 16 2.1 IsoFlux System 17 2.1.1 Microfluidic Design and Instrumentation 17 2.1.2 Clinical Blood Samples 18 2.1.3 Beads-EpCAM Coupling Reaction 19 2.1.4 Sample Preparation 19 2.1.5 CTCs Isolation 21 2.2 Immunofluorescence Staining 21 2.2.1 Principles of the Procedure 22 2.2.2 Sample Staining 22 2.3 High-Content Imaging 23 3. Results 25 3.1 Patients collection profile 26 3.2 High-content imaging for CTCs and WBCs 26 3.3 Identification of the correlation between CTCs and purity 28 3.4 Clinical correlation of CTCs with other peripheral blood cells 29 3.5 NLR as a disease progression indicator 31 3.6 Dynamic change of CTC count after the first treatment 33 3.7 Comparing multiple CTC counts among different disease courses 36 3.8 Clinical longitudinal monitoring with CTCs 38 4. Conclusions 41 5. Discussion 44 5.1 Discrepancy in CTC Enumeration 45 5.2 CTCs and peripheral blood cells 46 5.3 NLR and CTC count as potential markers 47 5.4 Longitudinal studies in liquid biopsies 48 5.5 Combined biomarkers in clinical applications 49 5.6 Correlation between CTCs and Metastasis 50 5.7 Increased CTC count after EGFR-TKIs treatment 51 5.8 Liquid biopsies of CTCs and cfDNA in NSCLC 53 6. Figures 55 Figure 1. Patients collection profile 56 Figure 2. Immunostaining fluorescent images under high-content imaging system. 57 Figure 3. Identification of the correlation between CTC count and purity after IsoFlux enrichment. 58 Figure 4. Clinical correlation of CTC count with other peripheral blood cells. 60 Figure 5. Correlation between CTCs and monocytes in different EGFR classification. 61 Figure 6. NLR might be a potential indicator of poor prognosis. 63 Figure 7. CTC count slightly decreased after the first standard chemotherapy. 64 Figure 8. CTC count dynamically changed after different TKIs treatment among EGFR mutations patients. 66 Figure 9. Comparing multiple CTC counts among different disease courses patients. 68 Figure 10. Longitudinal monitoring disease progression and therapy response with serial analyses of CTC count. 71 7. Supplementary figures 72 Supplementary Figure 1. Brain metastasis outcomes cohort 73 Supplementary Figure 2. CTCs morphology 74 Supplementary Figure 3. Longitudinal CTCs count and purity of indicated patients since the first treatment. 75 Supplementary Figure 4. Correlation between CTCs and monocytes proportion (Mono. %) in different EGFR classification. 76 Supplementary Figure 5. Further evaluation in initial brain metastasis patients. 77 Supplementary Figure 6. Trends of dynamic CTC count during six months before progressive disease. 79 Table 1. Comparing FDA approved EGFR TKIs with chemotherapy in Asia EGFR mutation positive advanced NSCLC patients. 80 8. References 81 | |
dc.language.iso | en | |
dc.title | 循環腫瘤細胞的動態變化於晚期非小細胞肺癌之縱向研究 | zh_TW |
dc.title | Dynamic Characterization of Circulating Tumor Cells in Advanced NSCLC: A Longitudinal Study | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇剛毅(Kang-Yi SU),華國泰(Kuo-Tai Hua),李明學(Ming-Shyue Lee) | |
dc.subject.keyword | 精準醫療,液態檢體,表皮生長因子受體酪氨酸,激?抑制劑,預後,中性球與淋巴球比值,NLR, | zh_TW |
dc.subject.keyword | precision medicine,liquid biopsy,epidermal growth factor receptor,EGFR-TKI,prognosis,neutrophil-to-lymphocyte ratio,NLR, | en |
dc.relation.page | 97 | |
dc.identifier.doi | 10.6342/NTU201801122 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-07-12 | |
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 |
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