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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 阮雪芬 | zh_TW |
| dc.contributor.advisor | Hsueh-Fen Juan | en |
| dc.contributor.author | NGUYEN HOANG PHUONG UYEN | zh_TW |
| dc.contributor.author | NGUYEN HOANG PHUONG UYEN | en |
| dc.date.accessioned | 2026-02-11T16:11:09Z | - |
| dc.date.available | 2026-02-12 | - |
| dc.date.copyright | 2026-02-11 | - |
| dc.date.issued | 2026 | - |
| dc.date.submitted | 2026-01-30 | - |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101537 | - |
| dc.description.abstract | 肺腺癌（LUAD）是肺癌中上普遍的一種亞型，其特徵是具有高度分子變異性佮病理生長型態的異質性。腫瘤相關巨噬細胞（TAMs）是腫瘤微環境（TME）中重要的細胞組成，會透過代謝重編程、免疫抑制以及細胞外基質重塑，展現促進腫瘤發展的功能，進一步形成纖維化的腫瘤環境佮治療抗性。然而，TAM 的起源多樣性、可塑性，以及佢佇腫瘤進程中如何驅動促腫瘤表型的機制，猶原無完全被釐清。
為著補足這个研究缺口，本研究整合公開資料庫中的單細胞轉錄體資料佮空間轉錄體資料，系統性分析 LUAD 中 TAM 的亞群組成、空間分佈佮細胞間互動，並評估其臨床相關性。 偽時間分析顯示，巨噬細胞主要呈現兩條分化軌跡：一條是佔據穩定分支的組織常駐型肺泡巨噬細胞（TRAMs），另一條則包含可能源自胚胎期巨噬細胞及循環單核球的 TAM 亞群。功能分析結果指出，TRAMs 主要存在佇正常肺組織中，負責維持組織恆定佮免疫監控；相對之下，腫瘤相關的 TAM 亞群則表現出適應低氧環境、促進血管新生佮細胞外基質重塑等促腫瘤特徵，與纖維化活性密切相關。 其中，SPP1 作為一種基質相關蛋白，主要高表現佇腫瘤富集的 TAM 亞群中，並與腫瘤惡性進展相關。進一步的細胞互動分析佮空間定位結果顯示，SPP1⁺TAMs 與癌症相關纖維母細胞（CAFs）會共同聚集佇腫瘤與基質交界區，形成支持促腫瘤發展的訊號網絡。存活分析進一步證實，高 SPP1 表現量以及 SPP1⁺ TAMs 與 CAFs 的共富集程度，皆與 LUAD 病患較差的臨床預後顯著相關。 總結來講，本研究指出 SPP1 可作為 TAM 亞群的重要代表性標記，並參與調控巨噬細胞佇低氧、血管新生及促纖維化腫瘤環境中的適應能力。SPP1⁺ TAMs 與 CAFs 佇腫瘤基質介面的空間共富集，是 LUAD 腫瘤生成過程中關鍵的細胞交互作用，亦與不良預後密切相關。本研究透過分子層級佮空間層級的整合分析，深化對 TAM–CAF 互動機制的理解，並為未來發展以 SPP1 為標的的治療策略，提供重要的研究基礎。 | zh_TW |
| dc.description.abstract | Lung adenocarcinoma (LUAD) is the one of most predominant form of lung cancer, exhibiting by heterogeneity in molecular alterations and pathological growth patterns. Tumor-associated macrophages (TAMs) represent a key cellular component in the tumor microenvironment (TME), exhibiting pro-tumor functions through metabolic reprogramming, immunosuppression, and extracellular matrix (ECM) remodeling, thereby promoting a profibrotic environment and therapeutic resistance. However, the diversity and plasticity of TAM ontogeny and the mechanisms by which they drive pro-tumor phenotypes during tumor progression remain incompletely understood. Addressing this knowledge gap, we integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data from the Gene Expression Omnibus (GEO) datasets, aimed to characterize TAM subpopulations, map their spatial distribution and interaction, and evaluate their clinical relevance in LUAD.
Pseudotime analysis identified two main differentiation trajectories: Tissue-resident alveolar macrophages (TRAMs) occupying a stable branch, alongside TAM subsets likely derived from both embryonic macrophages and circulating monocytes. Functional profiling revealed that TRAMs predominate in normal lung tissues largely maintain signatures of tissue homeostasis and immune surveillance functions; in contrast, TAM subpopulations display pro-tumorigenic phenotypes via hypoxia adaptation, angiogenesis, and ECM remodeling, consistent with profibrotic activity. Notably, SPP1 (Secreted Phosphoprotein 1), a matricellular protein related to epigenetic changes and reduced drug uptake, was dominantly expressed on tumor-enriched TAM subtypes. Cell-cell communication and spatial mapping detected the colocalization of SPP1+TAMs and cancer-associated fibroblasts (CAFs) at the tumor-stromal boundaries, with ligand–receptor signaling patterns that support pro-tumorigenic networks. Finally, survival analyses further validated that high SPP1 expression and higher inferred SPP1+TAMs-CAFs co-abundance associate with worse survival outcomes in LUAD. In conclusion, this study identified that SPP1 serves as a representative marker on TAM subpopulations, reprogramming the adaptive capability of macrophages in hypoxic, angiogenic, and pro-fibrotic tumor environ ments. The spatial co-enrichment of SPP1+TAMs and CAFs at the tumor-stromal interfaces represents a key cellular interaction in LUAD tumorigenesis linked to worse prognosis. The molecular profiling and advanced spatial analysis expand the insight of TAM-CAF crosstalk,and offer future exploration for SPP1-targeted therapies to counteract therapeutic resistance and enhance survival outcomes. Keywords: lung adenocarcinoma (LUAD), tumor microenvironment (TME), tumor-associated macrophages (TAMs), tissue-resident macrophage (TRAMs), single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), secreted phosphoprotein 1 (SPP1), cancer-associated fibroblasts (CAFs). | en |
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| dc.description.provenance | Made available in DSpace on 2026-02-11T16:11:09Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | ACKNOWLEDGEMENT i
摘要 ii ABSTRACT iv TABLE OF CONTENTS vi LIST OF FIGURES x LIST OF TABLES xii LIST OF ABBREVIATIONS xiv CHAPTER 1: INTRODUCTION 1 1.1 Overview of lung adenocarcinoma 1 1.2 Tumor microenvironment complexity in lung adenocarcinoma 2 1.3 Tumor-associated macrophages in lung adenocarcinoma 3 1.4 Heterogeneity of tumor-associated macrophages in lung adenocarcinoma 5 1.5 The interaction of tumor-associated macrophages and cancer-associated fibroblasts in lung adenocarcinoma progression 9 1.6 Integration of single-cell RNA sequencing and spatial transcriptomics data analysis 12 1.7 Research aims 14 CHAPTER 2: MATERIALS AND METHODS 16 2.1 Data acquisition 16 2.2 Quality control and processing scRNA-seq and spatial transcriptomics data 17 2.3 Annotation of scRNA-seq main cell populations 20 2.4 Sub-clustering macrophage populations 20 2.5 Differentially expressed gene (DEGs) analysis 21 2.6 Cell type composition analysis 22 2.6.1 Cell type abundance quantification 22 2.6.2 Generalized Linear Mixed-effects Modeling (GLMM) 23 2.7 Functional enrichment analysis 23 2.7.1 Gene Set Enrichment Analysis (GSEA) 23 2.7.2 Gene Set Variation Analysis (GSVA) 24 2.7.3 Macrophage-specific functional signature scoring 25 2.8 Pseudotime trajectory analysis 25 2.9 Cell-cell communication analysis 27 2.10 Spatial cell type annotation using gene signature scoring 28 2.11 Spatial deconvolution analysis of cell types 29 2.12 Spatial correlation analysis of TAMs and CAFs 29 2.13 Spatial interaction analysis of TAMs and CAFs 31 2.13.1 Cell type-weighted signaling score calculation 31 2.13.2 Co-localization analysis using Moran’s I autocorrelation 32 2.13.3 Tumor-stromal interface identification 33 2.13.4 Spatial functional gene signature analysis 33 2.14 Clinical validation using TCGA data 33 2.14.1 TCGA-based validation of TAM-CAF correlation 33 2.14.2 Survival analysis 34 2.15 Statistical analysis 36 CHAPTER 3: RESULTS 37 3.1 Single-cell profiling identifies macrophages as abundant immune cells in LUAD 37 3.2 Identification and characterization of macrophage subpopulations in LUAD 38 3.3 Differential distribution of macrophage subpopulations between conditions 38 3.4 Functional characterization of macrophage subpopulations in LUAD 40 3.4.1 KEGG pathway enrichment identifies subtype-related signaling programs 41 3.4.2 Hallmark gene set analysis reveals core biological activities 42 3.4.3 Differential expression of functional marker genes validates subtype identities 44 3.5 Pseudotime analysis reveals distinct differentiation pathways of macrophage subpopulations within the tumor microenvironment 46 3.5.1 CytoTRACE analysis identifies differentiation states across macrophage subtypes 46 3.5.2 Trajectory inference reveals branched differentiation pathways 47 3.5.3 Dynamic gene expression profiling characterizes molecular transitions along pseudotime 48 3.6 Cell-cell communication reveals tumor-specific SPP1-CD44 axis interactions between TAMs and CAFs 49 3.7 SPP1+TAMs are enriched in tumors and predict worse clinical prevalent 51 3.8 Spatial profiling and deconvolution validates cellular distributions 52 3.9 Spatial proximity and co-localization of SPP1+TAMs and CD44+CAFs in lung tumors 53 3.9.1 Spatial proximity of TAMs and CAFs 53 3.9.2 Co-localization quantification of SPP1+TAMs and CD44+CAFs 55 3.10 Functional signaling pathway activation at tumor-stromal interfaces 57 3.11 Clinical validation of TAM-CAF co-enrichment 58 CHAPTER 4: DISCUSSION 59 CHAPTER 5: CONCLUSION 64 FIGURES 65 TABLES 90 REFERENCES 91 | - |
| dc.language.iso | en | - |
| dc.subject | 肺腺癌 | - |
| dc.subject | 腫瘤微環境 | - |
| dc.subject | 腫瘤相關巨噬細胞 | - |
| dc.subject | 組織常駐型巨噬細胞 | - |
| dc.subject | 單細胞轉錄體 | - |
| dc.subject | 空間轉錄體 | - |
| dc.subject | 癌症相關纖維母細胞 | - |
| dc.subject | SPP1 | - |
| dc.subject | lung adenocarcinoma (LUAD) | - |
| dc.subject | tumor microenvironment (TME) | - |
| dc.subject | tumor-associated macrophages (TAMs) | - |
| dc.subject | tissue-resident macrophage (TRAMs) | - |
| dc.subject | single-cell RNA sequencing (scRNA-seq) | - |
| dc.subject | spatial transcriptomics (ST) | - |
| dc.subject | secreted phosphoprotein 1 (SPP1) | - |
| dc.subject | cancer-associated fibroblasts (CAFs) | - |
| dc.title | 單細胞與空間轉錄體學揭示肺腺癌中腫瘤相關巨噬細胞的異性及其與癌症相關成纖維細胞之鄰近交互作用 | zh_TW |
| dc.title | Single-Cell and Spatial Transcriptomics Unveil Heterogeneity of Tumor-Associated Macrophages and Their Proximity Interactions with Cancer-Associated Fibroblasts in Lung Adenocarcinoma | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 114-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 黃宣誠;許家郎 | zh_TW |
| dc.contributor.oralexamcommittee | Hsuan-Cheng Huang;Chia-Lang Hsu | en |
| dc.subject.keyword | 肺腺癌,腫瘤微環境腫瘤相關巨噬細胞組織常駐型巨噬細胞單細胞轉錄體空間轉錄體癌症相關纖維母細胞SPP1 | zh_TW |
| dc.subject.keyword | lung adenocarcinoma (LUAD),tumor microenvironment (TME)tumor-associated macrophages (TAMs)tissue-resident macrophage (TRAMs)single-cell RNA sequencing (scRNA-seq)spatial transcriptomics (ST)secreted phosphoprotein 1 (SPP1)cancer-associated fibroblasts (CAFs) | en |
| dc.relation.page | 101 | - |
| dc.identifier.doi | 10.6342/NTU202600290 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2026-02-02 | - |
| dc.contributor.author-college | 生命科學院 | - |
| dc.contributor.author-dept | 基因體與系統生物學學位學程 | - |
| dc.date.embargo-lift | 2030-01-30 | - |
| Appears in Collections: | 基因體與系統生物學學位學程 | |
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|---|---|---|---|
| ntu-114-1.pdf Restricted Access | 5.64 MB | Adobe PDF | View/Open |
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