請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97156完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳世淯 | zh_TW |
| dc.contributor.advisor | Shih-Yu Chen | en |
| dc.contributor.author | 李芷瑩 | zh_TW |
| dc.contributor.author | Tsz Ying Li | en |
| dc.date.accessioned | 2025-02-27T16:27:02Z | - |
| dc.date.available | 2025-02-28 | - |
| dc.date.copyright | 2025-02-27 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-02-13 | - |
| dc.identifier.citation | World Cancer Day 2024. World Health Organization - Regional Office for the Eastern Mediterranean. Retrieved December 7, 2024, from http://www.emro.who.int/media/news/world-cancer-day-2024.html
Anand, U., Dey, A., Chandel, A. K. S., Sanyal, R., Mishra, A., Pandey, D. K., De Falco, V., Upadhyay, A., Kandimalla, R., Chaudhary, A., Dhanjal, J. K., Dewanjee, S., Vallamkondu, J., & Pérez De La Lastra, J. M. (2023). Cancer chemotherapy and beyond: Current status, drug candidates, associated risks and progress in targeted therapeutics. Genes & Diseases, 10(4), 1367–1401. https://doi.org/10.1016/j.gendis.2022.02.007 van den Boogaard, W. M. C., Komninos, D. S. J., & Vermeij, W. P. (2022). Chemotherapy Side-Effects: Not All DNA Damage Is Equal. Cancers, 14(3), Article 3. https://doi.org/10.3390/cancers14030627 Egea, J., López-Muñoz, F., Fernández-Capetillo, O., Reiter, R. J., & Romero, A. (2022). Alkylating Agent-Induced Toxicity and Melatonin-Based Therapies. Frontiers in Pharmacology, 13, 873197. https://doi.org/10.3389/fphar.2022.873197 Camilli, M., Cipolla, C. M., Dent, S., Minotti, G., & Cardinale, D. M. (2024). Anthracycline Cardiotoxicity in Adult Cancer Patients. JACC: CardioOncology, 6(5), 655–677. https://doi.org/10.1016/j.jaccao.2024.07.016 Cardinale, D., Iacopo, F., & Cipolla, C. M. (2020). Cardiotoxicity of Anthracyclines. Frontiers in Cardiovascular Medicine, 7, 26. https://doi.org/10.3389/fcvm.2020.00026 Min, H.-Y., & Lee, H.-Y. (2022). Molecular targeted therapy for anticancer treatment. Experimental & Molecular Medicine, 54(10), 1670–1694. https://doi.org/10.1038/s12276-022-00864-3 Eiermann, W. (2001). Trastuzumab combined with chemotherapy for the treatment of HER2-positive metastatic breast cancer: Pivotal trial data. Annals of Oncology, 12, S57–S62. https://doi.org/10.1093/annonc/12.suppl_1.S57 Sawaki, M., Taira, N., Uemura, Y., Saito, T., Baba, S., Kobayashi, K., Kawashima, H., Tsuneizumi, M., Sagawa, N., Bando, H., Takahashi, M., Yamaguchi, M., Takashima, T., Nakayama, T., Kashiwaba, M., Mizuno, T., Yamamoto, Y., Iwata, H., Kawahara, T., … for the RESPECT study group. (2020). Randomized Controlled Trial of Trastuzumab With or Without Chemotherapy for HER2-Positive Early Breast Cancer in Older Patients. Journal of Clinical Oncology, 38(32), 3743–3752. https://doi.org/10.1200/JCO.20.00184 Ottmann, O. G., Wassmann, B., Pfeifer, H., Giagounidis, A., Stelljes, M., Dührsen, U., Schmalzing, M., Wunderle, L., Binckebanck, A., Hoelzer, D., & GMALL Study Group. (2007). Imatinib compared with chemotherapy as front-line treatment of elderly patients with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ALL). Cancer, 109(10), 2068–2076. https://doi.org/10.1002/cncr.22631 Dillman, R. O. (2011). Cancer immunotherapy. Cancer Biotherapy & Radiopharmaceuticals, 26(1), 1–64. https://doi.org/10.1089/cbr.2010.0902 Waldman, A. D., Fritz, J. M., & Lenardo, M. J. (2020). A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nature Reviews Immunology, 20(11), 651–668. https://doi.org/10.1038/s41577-020-0306-5 Sordo-Bahamonde, C., Lorenzo-Herrero, S., Gonzalez-Rodriguez, A. P., Martínez-Pérez, A., Rodrigo, J. P., García-Pedrero, J. M., & Gonzalez, S. (2023). Chemo-Immunotherapy: A New Trend in Cancer Treatment. Cancers, 15(11), 2912. https://doi.org/10.3390/cancers15112912 Emens, L. A., & Middleton, G. (2015). The Interplay of Immunotherapy and Chemotherapy: Harnessing Potential Synergies. Cancer Immunology Research, 3(5), 436–443. https://doi.org/10.1158/2326-6066.CIR-15-0064 Wolchok, J. D., Hodi, F. S., Weber, J. S., Allison, J. P., Urba, W. J., Robert, C., O’Day, S. J., Hoos, A., Humphrey, R., Berman, D. M., Lonberg, N., & Korman, A. J. (2013). Development of ipilimumab: A novel immunotherapeutic approach for the treatment of advanced melanoma. Annals of the New York Academy of Sciences, 1291(1), 1–13. https://doi.org/10.1111/nyas.12180 Ramirez-Salazar, E., Schenck, S., & Herlyn, M. (2022). Role of Immune Cells in the Tumor Microenvironment. In N. Rezaei (Ed.), Handbook of Cancer and Immunology (pp. 1–13). Springer International Publishing. https://doi.org/10.1007/978-3-030-80962-1_84-1 Vivier, E., Ugolini, S., Blaise, D., Chabannon, C., & Brossay, L. (2012). Targeting natural killer cells and natural killer T cells in cancer. Nature Reviews Immunology, 12(4), 239–252. https://doi.org/10.1038/nri3174 Long, E. O., Kim, H. S., Liu, D., Peterson, M. E., & Rajagopalan, S. (2013). Controlling NK Cell Responses: Integration of Signals for Activation and Inhibition. Annual Review of Immunology, 31, 10.1146/annurev-immunol-020711–075005. https://doi.org/10.1146/annurev-immunol-020711-075005 Bödder, J., Zahan, T., van Slooten, R., Schreibelt, G., de Vries, I. J. M., & Flórez-Grau, G. (2021). Harnessing the cDC1-NK Cross-Talk in the Tumor Microenvironment to Battle Cancer. Frontiers in Immunology, 11. https://doi.org/10.3389/fimmu.2020.631713 Xing, S., & Ferrari de Andrade, L. (2020). NKG2D and MICA/B shedding: A ‘tag game’ between NK cells and malignant cells. Clinical & Translational Immunology, 9(12), e1230. https://doi.org/10.1002/cti2.1230 Verron, Q., Forslund, E., Brandt, L., Leino, M., Frisk, T. W., Olofsson, P. E., & Önfelt, B. (2021). NK cells integrate signals over large areas when building immune synapses but require local stimuli for degranulation. Science Signaling, 14(684), eabe2740. https://doi.org/10.1126/scisignal.abe2740 Prager, I., & Watzl, C. (2019). Mechanisms of natural killer cell-mediated cellular cytotoxicity. Journal of Leukocyte Biology, 105(6), 1319–1329. https://doi.org/10.1002/JLB.MR0718-269R Ham, H., Medlyn, M., & Billadeau, D. D. (2022). Locked and Loaded: Mechanisms Regulating Natural Killer Cell Lytic Granule Biogenesis and Release. Frontiers in Immunology, 13, 871106. https://doi.org/10.3389/fimmu.2022.871106 Coënon, L., Geindreau, M., Ghiringhelli, F., Villalba, M., & Bruchard, M. (2024). Natural Killer cells at the frontline in the fight against cancer. Cell Death & Disease, 15(8), 1–14. https://doi.org/10.1038/s41419-024-06976-0 Wang, R., Jaw, J. J., Stutzman, N. C., Zou, Z., & Sun, P. D. (2012). Natural killer cell-produced IFN-γ and TNF-α induce target cell cytolysis through up-regulation of ICAM-1. Journal of Leukocyte Biology, 91(2), 299–309. https://doi.org/10.1189/jlb.0611308 Bennett-Boehm, M. M. C., Mahr, A. R., Hartwell, S. T., Regan, A. K., Weber, I. S., Blackmon, A., Bisson, C. R., Truong, A. N., Circo, B. A., Nienhueser, J., Rogers, D. R., Booher, N., Rajagopalan, N., Martens, J. W. S., & Denton, P. W. (2023). Development and implementation of natural killer cell simultaneous ADCC and direct killing assay. Heliyon, 9(12), e22991. https://doi.org/10.1016/j.heliyon.2023.e22991 Xie, N., Shen, G., Gao, W., Huang, Z., Huang, C., & Fu, L. (2023). Neoantigens: Promising targets for cancer therapy. Signal Transduction and Targeted Therapy, 8(1), 1–38. https://doi.org/10.1038/s41392-022-01270-x Bulliard, Y., Andersson, B. S., Baysal, M. A., Damiano, J., & Tsimberidou, A. M. (2023). Reprogramming T cell differentiation and exhaustion in CAR-T cell therapy. Journal of Hematology & Oncology, 16(1), 108. https://doi.org/10.1186/s13045-023-01504-7 Sabag, B., Puthenveetil, A., Levy, M., Joseph, N., Doniger, T., Yaron, O., Karako-Lampert, S., Lazar, I., Awwad, F., Ashkenazi, S., & Barda-Saad, M. (2024). Dysfunctional natural killer cells can be reprogrammed to regain anti-tumor activity. The EMBO Journal, 43(13), 2552–2581. https://doi.org/10.1038/s44318-024-00094-5 Antonioli, L., Pacher, P., Vizi, E. S., & Haskó, G. (2013). CD39 and CD73 in immunity and inflammation. Trends in Molecular Medicine, 19(6), 355–367. https://doi.org/10.1016/j.molmed.2013.03.005 Vignali, P. D. A., DePeaux, K., Watson, M. J., Ye, C., Ford, B. R., Lontos, K., McGaa, N. K., Scharping, N. E., Menk, A. V., Robson, S. C., Poholek, A. C., Rivadeneira, D. B., & Delgoffe, G. M. (2023). Hypoxia drives CD39-dependent suppressor function in exhausted T cells to limit antitumor immunity. Nature Immunology, 24(2), 267–279. https://doi.org/10.1038/s41590-022-01379-9 Scharping, N. E., Rivadeneira, D. B., Menk, A. V., Vignali, P. D. A., Ford, B. R., Rittenhouse, N. L., Peralta, R., Wang, Y., Wang, Y., DePeaux, K., Poholek, A. C., & Delgoffe, G. M. (2021). Mitochondrial stress induced by continuous stimulation under hypoxia rapidly drives T cell exhaustion. Nature Immunology, 22(2), 205–215. https://doi.org/10.1038/s41590-020-00834-9 Kennedy, P. R., Arvindam, U. S., Phung, S. K., Ettestad, B., Feng, X., Li, Y., Kile, Q. M., Hinderlie, P., Khaw, M., Huang, R.-S., Kaufman, M., Puchalska, P., Russell, A., Butler, J., Abbott, L., McClure, P., Luo, X., Lu, Q. T., Blazar, B. R., … Felices, M. (2024). Metabolic programs drive function of therapeutic NK cells in hypoxic tumor environments. Science Advances, 10(44), eadn1849. https://doi.org/10.1126/sciadv.adn1849 Fischer, K., Hoffmann, P., Voelkl, S., Meidenbauer, N., Ammer, J., Edinger, M., Gottfried, E., Schwarz, S., Rothe, G., Hoves, S., Renner, K., Timischl, B., Mackensen, A., Kunz-Schughart, L., Andreesen, R., Krause, S. W., & Kreutz, M. (2007). Inhibitory effect of tumor cell–derived lactic acid on human T cells. Blood, 109(9), 3812–3819. https://doi.org/10.1182/blood-2006-07-035972 Peralta, R. M., Xie, B., Lontos, K., Nieves-Rosado, H., Spahr, K., Joshi, S., Ford, B. R., Quann, K., Frisch, A. T., Dean, V., Philbin, M., Cillo, A. R., Gingras, S., Poholek, A. C., Kane, L. P., Rivadeneira, D. B., & Delgoffe, G. M. (2024). Dysfunction of exhausted T cells is enforced by MCT11-mediated lactate metabolism. Nature Immunology, 25(12), 2297–2307. https://doi.org/10.1038/s41590-024-01999-3 Long, Y., Gao, Z., Hu, X., Xiang, F., Wu, Z., Zhang, J., Han, X., Yin, L., Qin, J., Lan, L., Yin, F., & Wang, Y. (2018). Downregulation of MCT4 for lactate exchange promotes the cytotoxicity of NK cells in breast carcinoma. Cancer Medicine, 7(9), 4690–4700. https://doi.org/10.1002/cam4.1713 Lim, A. R., Rathmell, W. K., & Rathmell, J. C. (n.d.). The tumor microenvironment as a metabolic barrier to effector T cells and immunotherapy. eLife, 9, e55185. https://doi.org/10.7554/eLife.55185 Liu, J., Bai, Y., Li, Y., Li, X., & Luo, K. (2024). Reprogramming the immunosuppressive tumor microenvironment through nanomedicine: An immunometabolism perspective. eBioMedicine, 107, 105301. https://doi.org/10.1016/j.ebiom.2024.105301 Gao, Z., Feng, Y., Xu, J., & Liang, J. (2022). T-cell exhaustion in immune-mediated inflammatory diseases: New implications for immunotherapy. Frontiers in Immunology, 13. https://doi.org/10.3389/fimmu.2022.977394 Wong, W. K., Yin, B., Lam, C. Y. K., Huang, Y., Yan, J., Tan, Z., & Wong, S. H. D. (2022). The Interplay Between Epigenetic Regulation and CD8+ T Cell Differentiation/Exhaustion for T Cell Immunotherapy. Frontiers in Cell and Developmental Biology, 9. https://doi.org/10.3389/fcell.2021.783227 Blake, M. K., O’Connell, P., & Aldhamen, Y. A. (2023). Fundamentals to therapeutics: Epigenetic modulation of CD8+ T Cell exhaustion in the tumor microenvironment. Frontiers in Cell and Developmental Biology, 10. https://doi.org/10.3389/fcell.2022.1082195 Merino, A., Zhang, B., Dougherty, P., Luo, X., Wang, J., Blazar, B. R., Miller, J. S., & Cichocki, F. (2019). Chronic stimulation drives human NK cell dysfunction and epigenetic reprograming. The Journal of Clinical Investigation, 129(9), 3770–3785. https://doi.org/10.1172/JCI125916 Watowich, M. B., Gilbert, M. R., & Larion, M. (2023). T cell exhaustion in malignant gliomas. Trends in Cancer, 9(4), 270–292. https://doi.org/10.1016/j.trecan.2022.12.008 Xie, N., Shen, G., Gao, W., Huang, Z., Huang, C., & Fu, L. (2023). Neoantigens: Promising targets for cancer therapy. Signal Transduction and Targeted Therapy, 8(1), 1–38. https://doi.org/10.1038/s41392-022-01270-x Dean, I., Lee, C. Y. C., Tuong, Z. K., Li, Z., Tibbitt, C. A., Willis, C., Gaspal, F., Kennedy, B. C., Matei-Rascu, V., Fiancette, R., Nordenvall, C., Lindforss, U., Baker, S. M., Stockmann, C., Sexl, V., Hammond, S. A., Dovedi, S. J., Mjösberg, J., Hepworth, M. R., … Withers, D. R. (2024). Rapid functional impairment of natural killer cells following tumor entry limits anti-tumor immunity. Nature Communications, 15(1), 683. https://doi.org/10.1038/s41467-024-44789-z Jia, H., Yang, H., Xiong, H., & Luo, K. Q. (2023). NK cell exhaustion in the tumor microenvironment. Frontiers in Immunology, 14. https://doi.org/10.3389/fimmu.2023.1303605 Böttcher, J. P., Bonavita, E., Chakravarty, P., Blees, H., Cabeza-Cabrerizo, M., Sammicheli, S., Rogers, N. C., Sahai, E., Zelenay, S., & Reis E Sousa, C. (2018). NK Cells Stimulate Recruitment of cDC1 into the Tumor Microenvironment Promoting Cancer Immune Control. Cell, 172(5), 1022-1037.e14. https://doi.org/10.1016/j.cell.2018.01.004 Seo, H., Jeon, I., Kim, B.-S., Park, M., Bae, E.-A., Song, B., Koh, C.-H., Shin, K.-S., Kim, I.-K., Choi, K., Oh, T., Min, J., Min, B. S., Han, Y. D., Kang, S.-J., Shin, S. J., Chung, Y., & Kang, C.-Y. (2017). IL-21-mediated reversal of NK cell exhaustion facilitates anti-tumour immunity in MHC class I-deficient tumours. Nature Communications, 8, 15776. https://doi.org/10.1038/ncomms15776 Robert, C. (2020). A decade of immune-checkpoint inhibitors in cancer therapy. Nature Communications, 11(1), 3801. https://doi.org/10.1038/s41467-020-17670-y Davis, Z., Felices, M., Lenvik, T. R., Badal, S., Hinderlie, P., Blazar, B. R., Vallera, D. A., & Miller, J. S. (2019). PD-1 Is Expressed at Low Levels on All Peripheral Blood Natural Killer Cells but Is a Significant Suppressor of NK Function Against PD-1 Ligand Expressing Tumor Targets. Blood, 134(Supplement_1), 621. https://doi.org/10.1182/blood-2019-127261 Albelda, S. M. (2024). CAR T cell therapy for patients with solid tumours: Key lessons to learn and unlearn. Nature Reviews Clinical Oncology, 21(1), 47–66. https://doi.org/10.1038/s41571-023-00832-4 Martins, T. A., Kaymak, D., Tatari, N., Gerster, F., Hogan, S., Ritz, M.-F., Sabatino, V., Wieboldt, R., Bartoszek, E. M., McDaid, M., Gerber, A., Buck, A., Beshirova, A., Heider, A., Shekarian, T., Mohamed, H., Etter, M. M., Schmassmann, P., Abel, I., … Hutter, G. (2024). Enhancing anti-EGFRvIII CAR T cell therapy against glioblastoma with a paracrine SIRPγ-derived CD47 blocker. Nature Communications, 15(1), 9718. https://doi.org/10.1038/s41467-024-54129-w Huang, H., Yu, L., Weng, H., Zhang, W., Wang, Z., Wang, L., & Huang, H. (2024). Advances in CAR-T cell therapy for hematologic and solid malignancies: Latest updates from 2024 ESMO Congress. Journal of Hematology & Oncology, 17(1), 120. https://doi.org/10.1186/s13045-024-01639-1 Belk, J. A., Yao, W., Ly, N., Freitas, K. A., Chen, Y.-T., Shi, Q., Valencia, A. M., Shifrut, E., Kale, N., Yost, K. E., Duffy, C. V., Daniel, B., Hwee, M. A., Miao, Z., Ashworth, A., Mackall, C. L., Marson, A., Carnevale, J., Vardhana, S. A., & Satpathy, A. T. (2022). Genome-wide CRISPR screens of T cell exhaustion identify chromatin remodeling factors that limit T cell persistence. Cancer Cell, 40(7), 768-786.e7. https://doi.org/10.1016/j.ccell.2022.06.001 Kasmani, M. Y., Zander, R., Chung, H. K., Chen, Y., Khatun, A., Damo, M., Topchyan, P., Johnson, K. E., Levashova, D., Burns, R., Lorenz, U. M., Tarakanova, V. L., Joshi, N. S., Kaech, S. M., & Cui, W. (2023). Clonal lineage tracing reveals mechanisms skewing CD8+ T cell fate decisions in chronic infection. Journal of Experimental Medicine, 220(1), e20220679. https://doi.org/10.1084/jem.20220679 Rosenberg, J., & Huang, J. (2018). CD8+ T Cells and NK Cells: Parallel and Complementary Soldiers of Immunotherapy. Current Opinion in Chemical Engineering, 19, 9–20. https://doi.org/10.1016/j.coche.2017.11.006 Tang, F., Li, J., Qi, L., Liu, D., Bo, Y., Qin, S., Miao, Y., Yu, K., Hou, W., Li, J., Peng, J., Tian, Z., Zhu, L., Peng, H., Wang, D., & Zhang, Z. (2023). A pan-cancer single-cell panorama of human natural killer cells. Cell, 186(19), 4235-4251.e20. https://doi.org/10.1016/j.cell.2023.07.034 Martínez-Jiménez, F., Movasati, A., Brunner, S. R., Nguyen, L., Priestley, P., Cuppen, E., & Van Hoeck, A. (2023). Pan-cancer whole-genome comparison of primary and metastatic solid tumours. Nature, 618(7964), 333–341. https://doi.org/10.1038/s41586-023-06054-z Lo, H. C., Xu, Z., Kim, I. S., Pingel, B., Aguirre, S., Kodali, S., Liu, J., Zhang, W., Muscarella, A. M., Hein, S. M., Krupnick, A. S., Neilson, J. R., Paust, S., Rosen, J. M., Wang, H., & Zhang, X. H.-F. (2020). Resistance to natural killer cell immunosurveillance confers a selective advantage to polyclonal metastasis. Nature Cancer, 1(7), 709–722. https://doi.org/10.1038/s43018-020-0068-9 Mselle, T. F., Meadows, S. K., Eriksson, M., Smith, J. M., Shen, L., Wira, C. R., & Sentman, C. L. (2007). Unique characteristics of NK cells throughout the human female reproductive tract. Clinical Immunology, 124(1), 69–76. https://doi.org/10.1016/j.clim.2007.04.008 Albini, A., & Noonan, D. M. (2021). Decidual-Like NK Cell Polarization: From Cancer Killing to Cancer Nurturing. Cancer Discovery, 11(1), 28–33. https://doi.org/10.1158/2159-8290.CD-20-0796 Andreatta, M., Corria-Osorio, J., Müller, S., Cubas, R., Coukos, G., & Carmona, S. J. (2021). Interpretation of T cell states from single-cell transcriptomics data using reference atlases. Nature Communications, 12(1), 2965. https://doi.org/10.1038/s41467-021-23324-4 Carmonalab/ProjecTILs. (2024). [R]. Cancer Systems Immunology Lab. https://github.com/carmonalab/ProjecTILs (Original work published 2020)\\ Gulati, G. S., Sikandar, S. S., Wesche, D. J., Manjunath, A., Bharadwaj, A., Berger, M. J., Ilagan, F., Kuo, A. H., Hsieh, R. W., Cai, S., Zabala, M., Scheeren, F. A., Lobo, N. A., Qian, D., Yu, F. B., Dirbas, F. M., Clarke, M. F., & Newman, A. M. (2020). Single-cell transcriptional diversity is a hallmark of developmental potential. Science, 367(6476), 405–411. https://doi.org/10.1126/science.aax0249 Cai, M.-C., Zhao, X., Cao, M., Ma, P., Chen, M., Wu, J., Jia, C., He, C., Fu, Y., Tan, L., Xue, X., Yu, Z., & Zhuang, G. (2020). T-cell exhaustion interrelates with immune cytolytic activity to shape the inflamed tumor microenvironment. The Journal of Pathology, 251(2), 147–159. https://doi.org/10.1002/path.5435 Smoothed conditional means—Geom_smooth. (n.d.). Retrieved December 14, 2024, from https://ggplot2.tidyverse.org/reference/geom_smooth.html Loess Regression and Smoothing With R. (n.d.). Retrieved December 14, 2024, from https://r-statistics.co/Loess-Regression-With-R.html Fellows, E., Gil-Parrado, S., Jenne, D. E., & Kurschus, F. C. (2007). Natural killer cell–derived human granzyme H induces an alternative, caspase-independent cell-death program. Blood, 110(2), 544–552. https://doi.org/10.1182/blood-2006-10-051649 Duquette, D., Harmon, C., Zaborowski, A., Michelet, X., O’Farrelly, C., Winter, D., Koay, H.-F., & Lynch, L. (2023). Human Granzyme K Is a Feature of Innate T Cells in Blood, Tissues, and Tumors, Responding to Cytokines Rather than TCR Stimulation. The Journal of Immunology, 211(4), 633–647. https://doi.org/10.4049/jimmunol.2300083 Willinger, T., Freeman, T., Herbert, M., Hasegawa, H., McMichael, A. J., & Callan, M. F. C. (2006). Human Naive CD8 T Cells Down-Regulate Expression of the WNT Pathway Transcription Factors Lymphoid Enhancer Binding Factor 1 and Transcription Factor 7 (T Cell Factor-1) following Antigen Encounter In Vitro and In Vivo. The Journal of Immunology, 176(3), 1439–1446. https://doi.org/10.4049/jimmunol.176.3.1439 Sebzda, E., Zou, Z., Lee, J. S., Wang, T., & Kahn, M. L. (2008). Transcription factor KLF2 regulates the migration of naive T cells by restricting chemokine receptor expression patterns. Nature Immunology, 9(3), 292–300. https://doi.org/10.1038/ni1565 Papavassiliou, A. G., & Musti, A. M. (2020). The Multifaceted Output of c-Jun Biological Activity: Focus at the Junction of CD8 T Cell Activation and Exhaustion. Cells, 9(11), Article 11. https://doi.org/10.3390/cells9112470 Wang, X., Tao, X., Chen, P., Jiang, P., Li, W., Chang, H., Wei, C., Lai, X., Zhang, H., Pan, Y., Ding, L., Liang, Z., Cui, J., Shao, M., Teng, X., Gu, T., Wei, J., Kong, D., Si, X., … Huang, H. (2024). MEK inhibition prevents CAR-T cell exhaustion and differentiation via downregulation of c-Fos and JunB. Signal Transduction and Targeted Therapy, 9(1), 1–19. https://doi.org/10.1038/s41392-024-01986-y Seo, H., González-Avalos, E., Zhang, W., Ramchandani, P., Yang, C., Lio, C.-W. J., Rao, A., & Hogan, P. G. (2021). BATF and IRF4 cooperate to counter exhaustion in tumor-infiltrating CAR T cells. Nature Immunology, 22(8), 983–995. https://doi.org/10.1038/s41590-021-00964-8 Boi, S. K., Lan, X., & Youngblood, B. (2021). BATF targets T cell exhaustion for termination. Nature Immunology, 22(8), 936–938. https://doi.org/10.1038/s41590-021-00978-2 Martinez, G. J., Pereira, R. M., Äijö, T., Kim, E. Y., Marangoni, F., Pipkin, M. E., Togher, S., Heissmeyer, V., Zhang, Y. C., Crotty, S., Lamperti, E. D., Ansel, K. M., Mempel, T. R., Lähdesmäki, H., Hogan, P. G., & Rao, A. (2015). The Transcription Factor NFAT Promotes Exhaustion of Activated CD8+ T Cells. Immunity, 42(2), 265–278. https://doi.org/10.1016/j.immuni.2015.01.006 Ingram, J. T., Yi, J. S., & Zajac, A. J. (2011). Exhausted CD8 T Cells Downregulate the IL-18 Receptor and Become Unresponsive to Inflammatory Cytokines and Bacterial Co-infections. PLOS Pathogens, 7(9), e1002273. https://doi.org/10.1371/journal.ppat.1002273 Papavassiliou, A. G., & Musti, A. M. (2020). The Multifaceted Output of c-Jun Biological Activity: Focus at the Junction of CD8 T Cell Activation and Exhaustion. Cells, 9(11), Article 11. https://doi.org/10.3390/cells9112470 Dahabieh, M. S., DeCamp, L. M., Oswald, B. M., Kitchen-Goosen, S. M., Fu, Z., Vos, M., Compton, S. E., Longo, J., Williams, K. S., Ellis, A. E., Johnson, A., Sodiya, I., Vincent, M., Lee, H., Sheldon, R. D., Krawczyk, C. M., Yao, C., Wu, T., & Jones, R. G. (2024). NRF2-dependent regulation of the prostacyclin receptor PTGIR drives CD8 T cell exhaustion. bioRxiv, 2024.06.23.600279. https://doi.org/10.1101/2024.06.23.600279 Song, M., Sandoval, T. A., Chae, C.-S., Chopra, S., Tan, C., Rutkowski, M. R., Raundhal, M., Chaurio, R. A., Payne, K. K., Konrad, C., Bettigole, S. E., Shin, H. R., Crowley, M. J. P., Cerliani, J. P., Kossenkov, A. V., Motorykin, I., Zhang, S., Manfredi, G., Zamarin, D., … Cubillos-Ruiz, J. R. (2018). IRE1α–XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity. Nature, 562(7727), 423–428. https://doi.org/10.1038/s41586-018-0597-x Sun, Q., Zhao, X., Li, R., Liu, D., Pan, B., Xie, B., Chi, X., Cai, D., Wei, P., Xu, W., Wei, K., Zhao, Z., Fu, Y., Ni, L., & Dong, C. (2023). STAT3 regulates CD8+ T cell differentiation and functions in cancer and acute infection. Journal of Experimental Medicine, 220(4), e20220686. https://doi.org/10.1084/jem.20220686 Bannoud, N., Dalotto-Moreno, T., Kindgard, L., García, P. A., Blidner, A. G., Mariño, K. V., Rabinovich, G. A., & Croci, D. O. (2021). Hypoxia Supports Differentiation of Terminally Exhausted CD8 T Cells. Frontiers in Immunology, 12. https://doi.org/10.3389/fimmu.2021.660944 Staron, M. M., Gray, S. M., Marshall, H. D., Parish, I. A., Chen, J. H., Perry, C. J., Cui, G., Li, M. O., & Kaech, S. M. (2014). The Transcription Factor FoxO1 Sustains Expression of the Inhibitory Receptor PD-1 and Survival of Antiviral CD8+ T Cells during Chronic Infection. Immunity, 41(5), 802–814. https://doi.org/10.1016/j.immuni.2014.10.013 PubChem. (n.d.). RPL7—Ribosomal protein L7 (human). Retrieved December 13, 2024, from https://pubchem.ncbi.nlm.nih.gov/gene/RPL7/human Zinzalla, V., Stracka, D., Oppliger, W., & Hall, M. N. (2011). Activation of mTORC2 by Association with the Ribosome. Cell, 144(5), 757–768. https://doi.org/10.1016/j.cell.2011.02.014 Nawabi, H., & Belin, S. (2025). Translational machinery and translation regulation in axon regeneration. Neural Regeneration Research, 20(5), 1392. https://doi.org/10.4103/NRR.NRR-D-24-00313 Chen, R., Kang, R., & Tang, D. (2022). The mechanism of HMGB1 secretion and release. Experimental & Molecular Medicine, 54(2), 91–102. https://doi.org/10.1038/s12276-022-00736-w Yuan, S., Liu, Z., Xu, Z., Liu, J., & Zhang, J. (2020). High mobility group box 1 (HMGB1): A pivotal regulator of hematopoietic malignancies. Journal of Hematology & Oncology, 13(1), 91. https://doi.org/10.1186/s13045-020-00920-3 Kwak, M. S., Kim, H. S., Lee, B., Kim, Y. H., Son, M., & Shin, J.-S. (2020). Immunological Significance of HMGB1 Post-Translational Modification and Redox Biology. Frontiers in Immunology, 11. https://doi.org/10.3389/fimmu.2020.01189 Zheng, Y., Zhou, Z., Wei, R., Xiao, C., Zhang, H., Fan, T., Zheng, B., Li, C., & He, J. (2022). The RNA-binding protein PCBP1 represses lung adenocarcinoma progression by stabilizing DKK1 mRNA and subsequently downregulating β-catenin. Journal of Translational Medicine, 20, 343. https://doi.org/10.1186/s12967-022-03552-y Ansa-Addo, E. A., Huang, H.-C., Riesenberg, B., Iamsawat, S., Borucki, D., Nelson, M. H., Nam, J. H., Chung, D., Paulos, C. M., Liu, B., Yu, X.-Z., Philpott, C., Howe, P. H., & Li, Z. (2020). RNA binding protein PCBP1 is an intracellular immune checkpoint for shaping T cell responses in cancer immunity. Science Advances, 6(22), eaaz3865. https://doi.org/10.1126/sciadv.aaz3865 Garavís, M., & Calvo, O. (2017). Sub1/PC4, a multifaceted factor: From transcription to genome stability. Current Genetics, 63(6), 1023–1035. https://doi.org/10.1007/s00294-017-0715-6 Yu, L., Ma, H., Ji, X., & Volkert, M. R. (2016). The Sub1 nuclear protein protects DNA from oxidative damage. Molecular and Cellular Biochemistry, 412(1–2), 165–171. https://doi.org/10.1007/s11010-015-2621-x Feng, M., Xie, X., Han, G., Zhang, T., Li, Y., Li, Y., Yin, R., Wang, Q., Zhang, T., Wang, P., Hu, J., Cheng, Y., Gao, Z., Wang, J., Chang, J., Cui, M., Gao, K., Chai, J., Liu, W., … Zhang, H. (2021). YBX1 is required for maintaining myeloid leukemia cell survival by regulating BCL2 stability in an m6A-dependent manner. Blood, 138(1), 71–85. https://doi.org/10.1182/blood.2020009676 Kwon, E., Todorova, K., Wang, J., Horos, R., Lee, K. K., Neel, V. A., Negri, G. L., Sorensen, P. H., Lee, S. W., Hentze, M. W., & Mandinova, A. (2018). The RNA-binding protein YBX1 regulates epidermal progenitors at a posttranscriptional level. Nature Communications, 9(1), 1734. https://doi.org/10.1038/s41467-018-04092-0 Kim, S., Na, J. G., Hampsey, M., & Reinberg, D. (1997). The Dr1/DRAP1 heterodimer is a global repressor of transcription in vivo. Proceedings of the National Academy of Sciences of the United States of America, 94(3), 820–825. Yin, K., Peluso, M. J., Luo, X., Thomas, R., Shin, M.-G., Neidleman, J., Andrew, A., Young, K. C., Ma, T., Hoh, R., Anglin, K., Huang, B., Argueta, U., Lopez, M., Valdivieso, D., Asare, K., Deveau, T.-M., Munter, S. E., Ibrahim, R., … Roan, N. R. (2024). Long COVID manifests with T cell dysregulation, inflammation and an uncoordinated adaptive immune response to SARS-CoV-2. Nature Immunology, 25(2), 218–225. https://doi.org/10.1038/s41590-023-01724-6 Aran, D., Looney, A. P., Liu, L., Wu, E., Fong, V., Hsu, A., Chak, S., Naikawadi, R. P., Wolters, P. J., Abate, A. R., Butte, A. J., & Bhattacharya, M. (2019). Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nature Immunology, 20(2), 163–172. https://doi.org/10.1038/s41590-018-0276-y Raza, K. (2024). Introduction to Single-Cell RNA-seq Data Analysis. In K. Raza (Ed.), Machine Learning in Single-Cell RNA-seq Data Analysis (pp. 1–16). Springer Nature. https://doi.org/10.1007/978-981-97-6703-8_1 Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014). The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nature Biotechnology, 32(4), 381–386. https://doi.org/10.1038/nbt.2859 Street, K., Risso, D., Fletcher, R. B., Das, D., Ngai, J., Yosef, N., Purdom, E., & Dudoit, S. (2018). Slingshot: Cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics, 19(1), 477. https://doi.org/10.1186/s12864-018-4772-0 Kürten, C. H. L., Kulkarni, A., Cillo, A. R., Santos, P. M., Roble, A. K., Onkar, S., Reeder, C., Lang, S., Chen, X., Duvvuri, U., Kim, S., Liu, A., Tabib, T., Lafyatis, R., Feng, J., Gao, S.-J., Bruno, T. C., Vignali, D. A. A., Lu, X., … Ferris, R. L. (2021). Investigating immune and non-immune cell interactions in head and neck tumors by single-cell RNA sequencing. Nature Communications, 12(1), 7338. https://doi.org/10.1038/s41467-021-27619-4 Su, E. Y., Spangler, A., Bian, Q., Kasamoto, J. Y., & Cahan, P. (2022). Reconstruction of dynamic regulatory networks reveals signaling-induced topology changes associated with germ layer specification. Stem Cell Reports, 17(2), 427–442. https://doi.org/10.1016/j.stemcr.2021.12.018 Andreatta, M., Hérault, L., Gueguen, P., Gfeller, D., Berenstein, A. J., & Carmona, S. J. (2024). Semi-supervised integration of single-cell transcriptomics data. Nature Communications, 15(1), 872. https://doi.org/10.1038/s41467-024-45240-z Andreatta, M., Berenstein, A. J., & Carmona, S. J. (2022). scGate: Marker-based purification of cell types from heterogeneous single-cell RNA-seq datasets. Bioinformatics, 38(9), 2642–2644. https://doi.org/10.1093/bioinformatics/btac141 Ng, S. S., De Labastida Rivera, F., Yan, J., Corvino, D., Das, I., Zhang, P., Kuns, R., Chauhan, S. B., Hou, J., Li, X.-Y., Frame, T. C. M., McEnroe, B. A., Moore, E., Na, J., Engel, J. A., Soon, M. S. F., Singh, B., Kueh, A. J., Herold, M. J., … Engwerda, C. R. (2020). The NK cell granule protein NKG7 regulates cytotoxic granule exocytosis and inflammation. Nature Immunology, 21(10), 1205–1218. https://doi.org/10.1038/s41590-020-0758-6 Das, A. S., Basu, A., & Mukhopadhyay, R. (2024). Ribosomal proteins: The missing piece in the inflammation puzzle? Molecular and Cellular Biochemistry. https://doi.org/10.1007/s11010-024-05050-9 PFN1—Profilin-1—Homo sapiens (Human) | UniProtKB | UniProt. (n.d.). Retrieved January 22, 2025, from https://www.uniprot.org/uniprotkb/P07737/entry Ben-Shmuel, A., Sabag, B., Biber, G., & Barda-Saad, M. (2021). The Role of the Cytoskeleton in Regulating the Natural Killer Cell Immune Response in Health and Disease: From Signaling Dynamics to Function. Frontiers in Cell and Developmental Biology, 9. https://doi.org/10.3389/fcell.2021.609532 McGinnis, C. S., Murrow, L. M., & Gartner, Z. J. (2019). DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors. Cell Systems, 8(4), 329-337.e4. https://doi.org/10.1016/j.cels.2019.03.003 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97156 | - |
| dc.description.abstract | 自然殺手 (NK) 細胞在針對腫瘤的先天免疫反應中發揮至關重要的作用。長時間暴露於多重刺激會損害其效用功能 (effector functions) ，包括降低其對腫瘤細胞或病毒感染細胞的細胞毒性 (cytotoxicity) 並阻礙增生能力 (proliferation)，最終導致 NK 衰竭 (exhaustion)。
儘管如此，由於NK 細胞群有一定的異質性 (heterogeneity)，了解其潛在機制並準確定義NK 細胞衰竭表現型 (phenotype) 仍然是一個挑戰, 因為它不像CD8+ T 細胞般能直接利用T 細胞受體 (TCR) 作譜系追蹤 (lineage tracing)，這使得無法像對 T 細胞一樣精確追蹤 NK 細胞的衰竭過程 。因此，本研究旨在透過剖析 NK 細胞衰竭的複雜軌跡，並尋找能夠改善目前 NK用於癌症治療細胞移植的產品。 通過利用單細胞RNA測序（scRNA-seq）數據並重新應用CytoTRACE（Gulati et al，2020）來研究免疫細胞的衰竭 狀態，我成功重建了自然殺手細胞（NK）衰竭的軌跡，並解析了其進程中的轉錄變化。 這項研究揭示了腫瘤微環境中 NK 細胞衰竭的先前未被探索的機制，並識別出多個癌症資料集中的不同 DEGs 及其富集途徑。這項研究的主要發現包括與細胞毒性相關的 DEGs（例如 NKG7）、核糖體蛋白的意外角色（例如 RPS3），以及與肌動蛋白細胞骨架相關的基因（例如 PFN1、ARPC2），這些基因可能促進 NK 細胞衰竭期間的功能障礙。此外，六個轉錄因子，包括 HMGB1 和 PCBP1，被識別為可能調控 NK 細胞衰竭的因子，這些發現提供了新的見解及治療靶點，對於解決癌症中的免疫功能異常具有潛在意義。 | zh_TW |
| dc.description.abstract | Natural killer (NK) cells play a crucial role in the innate immune response against tumors. Prolonged exposure to multiple stimulants however would compromise their effector functions, ie. impaired their cytotoxic function and hampered anti-tumor capabilities, eventually leading to a state called NK exhaustion.
Still, understanding and defining NK cell exhaustion is challenging due to the heterogeneity of NK cells. In contrast to the well-characterized CD8+ T cells, which benefit from T cell receptor (TCR) lineage tracing, the lack of a similar mechanism in NK cells has hindered the ability to track their exhaustion progression. Therefore, this study aims to address this gap by dissecting the intricate trajectory of NK cell exhaustion and exploring potential strategies for enhancing current NK adoptive therapeutic products for cancer treatments. By utilizing single-cell RNA sequencing (scRNA-seq) data and repurposing CytoTRACE (Gulati et.al, 2020) for studying immune cell exhaustion, I was able to reconstruct NK exhaustion trajectory and dissect the transcriptional changes during its progression. This study reveals previously unexamined mechanisms of NK cell exhaustion within the tumor microenvironment, identifying distinct sets of DEGs and their enriched pathways across multiple cancer datasets. Key findings include DEGs linked to cytotoxicity (e.g., NKG7), unexpected roles of ribosomal proteins (e.g., RPS3), and actin cytoskeleton-related genes (e.g., PFN1, ARPC2), which may contribute to NK dysfunction during exhaustion. Additionally, six transcription factors, including HMGB1 and PCBP1, were identified as potential regulators of NK exhaustion, providing new insights and therapeutic targets for addressing immune dysfunction in cancer. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-02-27T16:27:02Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-02-27T16:27:02Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | i. Acknowledgements ⅰ
ii.中文摘要 ⅱ iii. English Abstract ⅲ iv. Graphical Abstract ⅳ v. Table Of Content ⅴ vi. List of Figures and Tables ⅷ List of Figures ⅷ List of Tables ⅹ List of Supplementary Table ⅹ vii. Abbreviations and Acronyms ⅺ 1. Literature Review 1 1.1 Cancer and their treatment strategies 1 1.1.1 Non-specificity of traditional cancer chemotherapeutic agents cause major side-effects 1 1.1.2 Emergence of targeted cancer therapy and immunotherapy 2 1.2 Immune Cells in the Tumor Microenvironment (TME) 4 1.3 Biology of NK cells 5 1.3.1 NK activation mechanism 5 1.3.2 NK’s Mechanisms of Tumor Cell Killing 6 1.4 Tumor microenvironment chronic stimulation to effector cells 9 1.5 Positive correlation between CD8+T cell differentiation and exhaustion 11 1.6 Current knowledge on NK exhaustion under chronic stimulation by viral infection and tumors 15 1.7 Single-cell RNA sequencing and trajectory inference analysis 17 2. Introduction 18 2.1 Background 18 2.2 Challenges in this study and potential solutions 19 2.2.1 Challenge 1: Difficulties in determining the precise activation time point of NK cells 19 2.2.2 Challenge 2: Difficulties in tracking the progression of NK exhaustion 21 2.2.3 Challenge 3: Incomplete understanding of NK cell exhaustion poses challenges in verifying the effectiveness and accuracy of the developed pipeline 22 2.3 Significances and potential impacts 24 2.4 Specific Aims 25 3. Methodology and Datasets 27 3.1 Datasets 27 3.2 Pipeline 28 3.2.1 (A) For Unannotated Dataset 29 3.2.1.1 Seurat scRNAseq analysis workflow 29 3.2.1.2 Cell Types Annotation 30 3.2.1.2.1 Single R for cell-type annotation 30 3.2.1.2.2 Refinement of subsetted cell types 31 3.2.1.3 Merging tumor lymphocytes and PBMC lymphocytes 32 3.2.1.4 ProjecTILs for mapping the CD8+ T cell exhaustion status 33 3.2.1 (B). Annotated dataset 34 3.2.2 CytoTRACE for inferring relative pseudotime in the exhaustion trajectory 35 3.2.3 CD8+T Exhaustion Score and NK Effector Function Scores 36 3.2.4 Statistical and Similarity Analyses 37 3.2.5 Data Smoothing 37 3.2.6 Identifications of DEGs between Exhaustion and Naive Groups 38 3.2.7 Pathway Enrichment Analysis 38 3.2.8 Epoch for GRN analysis 39 3.2.9 Data and Network Visualization 40 4. Results 42 4.1 Overview of Results 42 4.1.1 Cell Type Annotation and Visualization of Peripheral Blood and Tumor-Infiltrating Immune Cells 43 4.1.1.1 SingleR annotations of GSE164690 datasets 43 4.1.1.2 ProjecTILs annotation on CD8+T cells in GSE164690 datasets 43 4.1.1.3 Annotation from the GSE212890 44 4.2 Proof-of-concept: Using CD8+ T cells to validate CytoTRACE for studying immune cell exhaustion in tumor microenvironment 45 4.2.1 Relationship between CytoTRACE score and CD8+T exhaustion score and whether CytoTRACE can capture the CD8+T exhaustion trajectory 45 4.2.1.1 Relationship between CytoTRACE score and CD8+T exhaustion score 45 4.2.1.2 ProjecTILs projected CD8+T exhaustion states 47 4.2.2.3 Comparison between CD8+T exhaustion-score-derived groups and CytoTRACE-score derived groups 51 4.3 Application of CytoTRACE on NK exhaustion and identifying the turning point of NK exhaustion 53 4.3.1 Evaluation parameters for the fitness of using CytoTRACE to study NK exhaustion 53 4.3.1.1 Comparison between the CytoTRACE score of PBMC or normal-adjacent and tumor NK 53 4.3.1.2 Expression of NK effector function marker genes along CytoTRACE score 55 4.3.2 Identification of the “Turning point” for NK exhaustion 56 4.4 Identification of NK exhaustion-associated DEGs and their key biological pathways based on the identified exhaustion turning point. 58 4.4.1 Stringent: Common NK-exhaustion-associated DEGs between 4 cancer datasets (p-adj. Bonferroni < 0.05) 59 4.4.1.1 DEGs NK exhaustion DEGs from stringent criteria 60 4.4.1.2 Pathway enrichment from NK exhaustion DEGs found with stringent criteria 61 4.4.2 Lenient 1: Common NK-exhaustion-associated DEGs between 2 epithelial cancer datasets (p-adj. BH FDR < 0.05) 62 4.4.2.1 DEGs NK exhaustion DEGs from Lenient 1 criteria 62 4.4.2.2 Pathway enrichment from NK exhaustion DEGs found with lenient 1 criteria 63 4.4.3 Lenient 2: Common NK-exhaustion-associated DEGs between 4 cancer datasets (p-adj. BH FDR < 0.05) 64 4.4.3.1 DEGs NK exhaustion DEGs from Lenient 2 criteria 65 4.4.3.2 Pathway enrichment from NK exhaustion DEGs found with lenient 2 criteria 65 4.5 Inferring the upstream transcription factor regulating exhaustion-associated DEGs from gene-regulatory network analysis 66 4.5.1 Validation and application of a novel GRN analysis pipeline for identifying potential inhibitory targets on CD8+T cell exhaustion 67 4.5.1.1 Top regulators in epoch identified TF for naive and exhausted CD8+T 67 4.5.1.2 GRN analysis pipeline on CD8+T cells 70 4.5.2 Application of the GRN analysis pipeline on NK exhaustion related DEGs found with stringent criteria 75 4.5.3 Application of the GRN analysis pipeline on NK exhaustion related DEGs found with lenient 1 criteria 77 4.5.4 Application of the GRN analysis pipeline on NK exhaustion related DEGs found with lenient 2 criteria 79 5. Discussion 81 5.1 Overview 81 5.2 Known functions of the potential NK exhaustion inhibition targets 82 5.3 Therapeutic implications of potential NK exhaustion targets 85 5.4 Future Studies 86 5.5 Strengths of this project 87 5.6 Contributions to the Field 88 5.7 Limitations 90 6. Conclusion 92 7. References 93 8. Appendices 99 | - |
| dc.language.iso | en | - |
| dc.subject | CytoTRACE | zh_TW |
| dc.subject | 自然殺手細胞異質性 | zh_TW |
| dc.subject | 自然殺手細胞細胞毒性 | zh_TW |
| dc.subject | 單細胞 RNA 定序 | zh_TW |
| dc.subject | 自然殺手細胞 | zh_TW |
| dc.subject | Single-cell RNA Sequencing | en |
| dc.subject | NK Cytotoxicity | en |
| dc.subject | scRNA-seq | en |
| dc.subject | NK Cell Heterogeneity | en |
| dc.subject | Natural Killer Cells | en |
| dc.subject | NK Cell | en |
| dc.subject | CytoTRACE | en |
| dc.title | 解碼驅動自然殺手細胞衰竭軌跡之分子機制 | zh_TW |
| dc.title | Deciphering the Molecular Mechanism Driving Natural Killer (NK) Cell Exhaustion Trajectory | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 張耀明 | zh_TW |
| dc.contributor.coadvisor | Yao-Ming Chang | en |
| dc.contributor.oralexamcommittee | 高承福;張家銘 | zh_TW |
| dc.contributor.oralexamcommittee | Cheng-Fu Kao;Jia-Ming Chang | en |
| dc.subject.keyword | 自然殺手細胞,CytoTRACE,單細胞 RNA 定序,自然殺手細胞細胞毒性,自然殺手細胞異質性, | zh_TW |
| dc.subject.keyword | Natural Killer Cells,NK Cell,CytoTRACE,Single-cell RNA Sequencing,scRNA-seq,NK Cytotoxicity,NK Cell Heterogeneity, | en |
| dc.relation.page | 103 | - |
| dc.identifier.doi | 10.6342/NTU202500484 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2025-02-13 | - |
| 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 | 2030-02-06 | - |
| 顯示於系所單位： | 基因體與系統生物學學位學程 | |
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