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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 莊曜宇(Eric Y. Chuang) | |
| dc.contributor.author | Chia-Hsin Wu | en |
| dc.contributor.author | 吳佳興 | zh_TW |
| dc.date.accessioned | 2022-11-24T09:26:46Z | - |
| dc.date.available | 2022-11-24T09:26:46Z | - |
| dc.date.copyright | 2021-11-05 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2021-10-22 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81753 | - |
| dc.description.abstract | 次世代定序技術的發展、進階生醫資訊學方法的出現和大量累積的基因體數據，使得癌症基因體學的研究能得以實現，為腫瘤生物學及腫瘤病因學的領域發展開創了新的前景。本論文應用上述癌症基因體學的分析方法，以探討癌症中大片段的體細胞變異事件及癌症的演化軌跡，同時建立一套整合型的生醫資訊學分析套件，以利癌症基因體學的研究及分析。 過去的研究表示，不同乳癌亞型間好發的短片段變異及拷貝數變異皆有所差異，這也使得我們能夠假設更大片段的體細胞變異事件同樣也可能解釋乳癌亞型間的異質性。本論文首先使用116對台灣女性乳癌病人的全外顯子定序資料進行分析，除了找出驅動基因(driver genes)外，更進一步地探討全基因體倍增(whole-genome doubling; WGD)現象在不同乳癌亞型間的差異與影響，從而揭示出其與同源重組缺陷(homologous recombination deficiency; HRD)的關聯。三陰性乳癌最常出現全基因體倍增的現象，進而導致高度染色體不穩定性(chromosomal instability; CIN)。同時與管狀型乳癌相比，第二型人類上皮成長因子接受器蛋白過度表現型(HER2-enriched)乳癌發生全基因體倍增現象的時間相對較早，其腫瘤間染色體不穩定性的差異幅度也較廣泛。綜觀上述結果，染色體倍增現象的差異，同時影響同源重組缺陷的程度，也讓我們更進一步地了解台灣乳癌亞型間的腫瘤異質性，同時能更深入地了解癌症的潛在病因。 儘管對於原發病變進行適當的治療，仍然有5至10%的乳癌病人在發病後的十年內出現同側乳癌復發(ipsilateral breast tumor relapse; IBTR)的現象。因此本研究的第二個目標是對10位同側復發的乳癌病人之原發、復發和正常組織檢體進行全外顯子定序分析，以探討乳癌細胞的演化軌跡如何反映出同側乳癌復發的進展。我們發現原發及其同側復發的腫瘤間具有不同程度的同源重組缺陷、染色體不穩定性及體細胞驅動變異，並且進一步地推論出三種主要的癌症復發演化模型，分別反映出不同的突變過程及亞克隆多樣性(subclonal diversification)。最後此研究將可採取治療措施之生物標記(actionable biomarkers)與克隆結構(clonal architectures)的概念相結合，提出一個治療管理的框架，以期改善未來的治療策略。 本論文最後的研究重點，在於開發一套更加全面的體細胞突變分析套件MutScape，可用於全外顯子、全基因體定序和基因套組(gene panels)的資料上，使研究人員從各類體細胞突變之辨識工具中獲取突變資料時，能輕鬆地探索研究群體的突變特徵。此套件納入多種變異篩選及資料合併的功能，以快速排除錯誤辨識出的突變，並且執行資料註解及轉換。MutScape同時提供9種常見和進階的分析功能，並且能產生相對應的高解析度視覺化圖形，幫助研究人員進一步探索分析結果。最後，我們證明了MutScape能夠從已發表的研究及其定序資料中，正確地再現已知的研究結果，並且可透過進階的分析功能，找出過去癌症基因體學研究中尚未揭露的新發現。 整體而言，本論文的三個研究建立在癌症基因體學的方法架構下，利用次世代定序技術及生醫資訊學的演算法，發現台灣女性乳癌在不同亞型下，受到全基因體倍增的影響程度皆有所差異，同時其現象也與同源重組缺陷有所關聯。另外我們也進一步推論出三個主要的同側乳癌復發演化模型，結合藥物資訊的註解結果，提出一套改善治療管理的架構。最後則是開發出一套癌症基因體學的整合型分析套件，協助研究人員或剛入門的生物資訊分析人員，能輕鬆地進行相關的分析及研究。透過本論文的發現及方法，相信能使臨床研究人員對於台灣女性乳癌有更進一步地了解，以及能更有效率地進行癌症基因體學分析，從而達到精準醫療的目標。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T09:26:46Z (GMT). No. of bitstreams: 1 U0001-2210202101222200.pdf: 17092418 bytes, checksum: 36928821f1d8edb951a66d0d015f073f (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | "中文摘要 i Abstract iii Table of Contents v List of Figures viii List of Tables x Chapter 1. Introduction 1 1.1. Next-generation sequencing applications in cancer genomics 2 1.2. Advanced study designs in cancer genomics 6 1.3. Specific aims 8 1.4. Table 11 Chapter 2. Differential Whole-genome Doubling and Homologous Recombination Deficiencies across Breast Cancer Subtypes from the Taiwanese Population 12 2.1. Abstract 12 2.2. Introduction 13 2.3. Methods 16 2.3.1. Study population and specimens 16 2.3.2. Exome capture, library construction, and sequencing 17 2.3.3. Sequencing data processing 18 2.3.4. Variant calling 18 2.3.5. Discovery strategy for significantly mutated genes 20 2.3.6. Mutational signature analysis 21 2.3.7. Allele-specific copy number profiling 23 2.3.8. Assessment of BCTW sample quality 24 2.3.9. WGD and CIN 25 2.3.10. Clonality of somatic alterations and timing of WGD 26 2.3.11. HRD analysis 27 2.3.12. Statistics and reproducibility 28 2.4. Results 28 2.4.1. Patient characteristics 28 2.4.2. Mutational landscape of BCTW samples 29 2.4.3. WGD and CIN in breast cancer subtypes 32 2.4.4. Clonality and timing of driver events within subtypes 33 2.4.5. WGD with HRD 35 2.4.6. WGD with alternative DSB repair processes 36 2.5. Discussion 37 2.6. Figures 44 2.7. Table 54 Chapter 3. Evolutionary Trajectories and Genomic Divergence in Localized Breast Cancers after Ipsilateral Breast Tumor Recurrence 56 3.1. Abstract 56 3.2. Introduction 57 3-3. Methods 59 3.3.1. Study population and specimens 59 3.3.2. Exome capture, library construction, and sequencing 60 3.3.3. Sequencing data processing and quality assessment 61 3.3.4. Variant calling and post-processing strategies 62 3.3.5. Subclonal copy number assessment 64 3.3.6. Large-scale genomic events analysis 65 3.3.7. Assessment of bi-allelic alterations in HR-related genes 66 3.3.8. Potential driver and actionable gene identification in primary and relapsed lesions 67 3.3.9. Reconstruction of cancer clonal architecture 68 3.3.10. Trunk and branch alteration classification and clonal architecture labeling 68 3.3.11. Subclonal diversity assessment 69 3.3.12. Mutational signature analysis 70 3.3.13. Statistical analysis 71 3.4. Results 71 3.4.1. Overview of patient cohorts 71 3.4.2. HRD and CIN during BC evolution 72 3.4.3. Somatic drivers of relapse 75 3.4.4. Clonal architecture BC progression 76 3.4.5. Evolution of the mutational processes over time 80 3.4.6. Integration of actionability and tumor evolution in therapeutic decisions 81 3.5. Discussion 84 3.6. Figures 91 3.7. Tables 106 Chapter 4. MutScape: an analytical toolkit for probing the mutational landscape in cancer genomics 114 4.1. Abstract 114 4.2. Introduction 115 4-3. Methods 118 4.3.1. Data preprocessing module 118 4.3.2. Analysis and visualization module 122 4.4. Results 126 4.4.1. Mutational landscape discovery with the CoMut plot 126 4.4.2. Mutational signature analysis 128 4.4.3. Large-scale genomic events analysis 130 4.4.4. Actionable biomarker annotation 132 4.5. Discussion 132 4.6. Figures 137 4-7. Table 151 Chapter 5. Future directions 152 References 155 Appendix 166" | |
| dc.language.iso | en | |
| dc.subject | 乳癌 | zh_TW |
| dc.subject | 同側乳癌復發 | zh_TW |
| dc.subject | 癌症基因體學 | zh_TW |
| dc.subject | 體細胞變異 | zh_TW |
| dc.subject | 分析套件 | zh_TW |
| dc.subject | 癌症演化 | zh_TW |
| dc.subject | somatic alteration | en |
| dc.subject | analytics toolkit | en |
| dc.subject | cancer evolution | en |
| dc.subject | Cancer genomics | en |
| dc.subject | breast cancer | en |
| dc.subject | ipsilateral breast tumor relapse | en |
| dc.title | 通過突變事件和演化軌跡了解癌症基因體學 | zh_TW |
| dc.title | Understanding Cancer Genomics through Mutational Events and Evolutionary Trajectories | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 賴亮全(Hsin-Tsai Liu),蔡孟勳(Chih-Yang Tseng),阮雪芬,張金堅,侯明鋒,黃俊升 | |
| dc.subject.keyword | 癌症基因體學,乳癌,同側乳癌復發,體細胞變異,癌症演化,分析套件, | zh_TW |
| dc.subject.keyword | Cancer genomics,breast cancer,ipsilateral breast tumor relapse,somatic alteration,cancer evolution,analytics toolkit, | en |
| dc.relation.page | 167 | |
| dc.identifier.doi | 10.6342/NTU202104007 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2021-10-23 | |
| 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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