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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 阮雪芬(Hsueh-Fen Juan) | |
| dc.contributor.author | Hao-Chun Chang | en |
| dc.contributor.author | 張皓鈞 | zh_TW |
| dc.date.accessioned | 2021-06-16T06:35:56Z | - |
| dc.date.available | 2021-08-01 | |
| dc.date.copyright | 2020-08-04 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-07-28 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57139 | - |
| dc.description.abstract | 隨著免疫療法的進展，許多療法都有相當大的進展。但是這些療法的成效受到癌症腫瘤所創造出的微環境很大的影響，為了瞭解癌症腫瘤微環境裡面，腫瘤和周遭的免疫細胞的交互作用，在本研究中我們根據TCGA中腫瘤樣本裡免疫和基質細胞的組成，來重新將癌症腫瘤分成四種免疫亞型：分別為發炎型(S1)、毒殺細胞型(S2)、淋巴細胞耗竭型(S3)以及中性粒細胞型(S4)。我們分別探討了這四種免疫亞型的各種特性，包含：基因變異、免疫調節基因、病人預後等等。我們發現淋巴細胞耗竭型有較差的預後，而毒殺細胞型有較好的預後且有很高的突變負荷。我們還另外發現了一些特定已知的主導基因，例如BRAF 和CTNNB1 (和免疫細胞排除有關)的突變有分別顯著出現在發炎型和淋巴細胞耗竭型，另外還有TP53、TGFBR2和KRAS的突變顯著出現在中性粒細胞型。透過分析33種癌症的腫瘤樣本，我們找出和腫瘤微環境有關的基因突變以及變異的生物路徑。根據這些結果，我們希望有助於深入了解哪些異常突變會影響不同腫瘤微環境的形成。 | zh_TW |
| dc.description.abstract | With the advent of immunotherapy, it is essential to understand the interactions between tumors and cells in the tumor microenvironment. We estimated the abundance of ten im-mune and two stromal cell populations in all TCGA tumor samples from transcriptomic data. Based on the microenvironment composition across all tumor types, we identified four consensus immune subtypes: (S1) inflammatory, (S2) cytotoxic dominant, (S3) lymphocyte depleted, and (S4) neutrophil dominant. The four immune subtypes were further characterized by mutation, expression of immunomodulatory genes, and prognosis. The lymphocyte-depleted subtype had less favorable outcomes, while cytotoxic-dominant subtype had a better prognosis and higher average mutation load. Specific driver genes correlated with immune subtypes, such as BRAF and CTNNB1 mutations were observed over-representatively in high and low leukocyte-infiltrating subtypes S1 and S3, respec-tively, where CTNNB1 has been demonstrated that its activation is correlated with immune exclusion. In addition, TP53, TGFBR2, and KRAS mutations are significantly enriched in the neutrophil dominant subtype. In this study, we analyzed data with 33 diverse cancer types to identify the tumor micro-environment-associated genes and related dysfunctional pathways. The results provide insight into how genetic aberration shapes the tumor microenvironment. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T06:35:56Z (GMT). No. of bitstreams: 1 U0001-2207202016040500.pdf: 12632445 bytes, checksum: d341b9ab2378be11255c85c294de0a69 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 致謝 ii 中文摘要 iii ABSTRACT iv CONTENTS v LIST OF FIGURES ix LIST OF TABLES xi Chapter 1 Introduction 1 1.1 Cancer immunotherapy 1 1.2 Tumor Microenvironment 2 1.3 Estimation of Cell Abundance within the Tumor Microenvironments 4 1.4 Molecular Cancer Subtypes 5 1.5 Our Aims 7 Chapter 2 Materials and Methods 8 2.1 Clinical and Expression Data 8 2.2 Immune Subtype Identification 8 2.2.1 Marker Genes for Immune and Stroma Cell Types 8 2.2.2 Pan-cancer Profiling and Clustering 9 2.2.3 Exploratory Analysis of Tumor Microenvironment 10 2.2.4 Selecting the Optimal Number of Components 10 2.2.5 Tuning Regularization Weight Based on Cluster Stability 11 2.2.6 Validation with Model-based Clustering 12 2.3 Characterization of Immune Subtypes 13 2.3.1 Exploratory Analysis 13 2.3.2 Prognostic Analysis 13 2.3.3 Immunomodulator Expression Analysis 14 2.3.4 Comparison with The Immune Landscape of Cancer 14 2.4 Mutation Over-representation Analysis 15 2.4.1 Gene Level 15 2.4.2 Pathway Level 15 2.4.3 Copy Number Variation Analysis 16 2.5 Genomic Viral Content Analysis 17 2.6 Protein-Protein Interaction Network Analysis 18 2.7 Stratification of Immune Subtypes by Gene Signatures 18 2.8 Statistical Analysis 19 Chapter 3 Results 20 3.1 Portrayal of the Tumor Microenvironment with Transcriptomic Markers 20 3.2 Immune Subtypes in Cancer 21 3.2.1 Immune Subtypes have Distinct Cell Composition and Prognosis 21 3.2.2 Different Immuno-modulators Expressed in Immune Subtypes 22 3.2.3 Our Immune Subtypes Provide Complementary View 23 3.3 Genetic Aberrations and Dysfunctional Pathways in Immune Subtypes 25 3.3.1 S1 Inflammatory Subtype 26 3.3.2 S2 Cytotoxic-dominant Subtype 27 3.3.3 S3 Lymphocyte-depleted Subtype 30 3.3.4 S4 Neutrophil-dominant Subtype 31 3.4 Further Stratification of S2 and S4 Subtype 33 Chapter 4 Discussion 36 4.1 Summary of Pan-cancer Analysis of the TME 36 4.1.1 Characterization of the TME Corresponds to Previous Studies 36 4.1.2 Focusing on the Genetic Aberrations in Multiple Levels 37 4.1.3 Stratification beyond Immune Subtypes 38 4.2 Comparison between Tumor Mutations and CRISPR Screening Studies 39 4.3 Improvements of Defining Tumor Microenvironments 40 4.3.1 Limitations of Identifying the Immune Subtypes 40 4.3.2 Limitations of Mutational Over-representation Analysis 41 Chapter 5 Conclusions 42 REFERENCES 43 Figures 56 Tables 76 | |
| dc.language.iso | en | |
| dc.subject | 系統性全癌分析 | zh_TW |
| dc.subject | 癌症基因學 | zh_TW |
| dc.subject | 免疫亞型 | zh_TW |
| dc.subject | 腫瘤微環境 | zh_TW |
| dc.subject | 癌症免疫療法 | zh_TW |
| dc.subject | 基因突變 | zh_TW |
| dc.subject | systematic pan-cancer analysis | en |
| dc.subject | gene mutation | en |
| dc.subject | immuno-oncology | en |
| dc.subject | cancer genomics | en |
| dc.subject | immune subtypes | en |
| dc.subject | tumor microenvironment | en |
| dc.title | 以系統性全癌分析探討腫瘤突變與腫瘤微環境的關係 | zh_TW |
| dc.title | Systematic pan-cancer analysis reveals the associations of tumor mutations and microenvironment | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.author-orcid | 0000-0001-6880-656X | |
| dc.contributor.coadvisor | 歐陽彥正(Yen-Jen Oyang) | |
| dc.contributor.oralexamcommittee | 許家郎(Chia-Lang Hsu),黃宣誠(Hsuan-Cheng Huang),蔡懷寬(Huai-Kuang Tsai) | |
| dc.subject.keyword | 癌症基因學,腫瘤微環境,系統性全癌分析,免疫亞型,癌症免疫療法,基因突變, | zh_TW |
| dc.subject.keyword | cancer genomics,tumor microenvironment,systematic pan-cancer analysis,immune subtypes,immuno-oncology,gene mutation, | en |
| dc.relation.page | 92 | |
| dc.identifier.doi | 10.6342/NTU202001742 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-07-28 | |
| 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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