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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 阮雪芬(Hsueh-Fen Juan) | |
| dc.contributor.author | Chantal Hoi Yin Cheung | en |
| dc.contributor.author | 張海姸 | zh_TW |
| dc.date.accessioned | 2021-06-17T03:13:26Z | - |
| dc.date.available | 2023-07-19 | |
| dc.date.copyright | 2018-07-19 | |
| 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/123456789/69346 | - |
| dc.description.abstract | 多體學方法啟動了癌症研究的時代，加強了我們對生物系統複雜的相互作用之理解，並試圖揭示其潛在的分子機制，與辨認治療標的。我們利用整合磷酸化蛋白質體和蛋白質體進行了多維蛋白質體學方法，進而去揭露肺癌的功能網絡。MCM2是DNA複製起點的許可因子，並能幫助DNA解旋。 然而，肺癌細胞中透過蛋白質磷酸化的MCM2生物網絡仍然未開拓。藉由蛋白質體學技術，我們辨認到了753個磷酸化蛋白上的2361個磷酸化位點，和4672個蛋白，並發現MCM2的失調與肺癌細胞增生、細胞週期和遷移息息相關。 此外，我們發現HMGA1S99磷酸化在MCM2兩極化的擾動下表現出相反的結果，並且在調節肺癌細胞增生中扮演關鍵的角色。因此，這種多維蛋白質體學方法提升了我們對於治療性標的癌症特異性磷酸化蛋白的能力。
MYCN基因的擴增與腫瘤的產生和發展有關，並發生在約20% 神經母細胞瘤（NB），而其潛在的機制仍然難以捉摸。在本研究中，我們使用ChIP-seq和NB患者的基因表達綜合數據庫 (GEO) 去整合與MYCN結合的啟動子區域；當MYCN擴增（MNA）時，MTHFD2和PAICS的表現量顯著上調，並且我們發現MTHFD2和PAICS是受MYCN直接轉錄調控的基因，在NB的組織樣本和細胞株中皆呈正相關。進行標靶代謝體學研究使我們發現MNA NB細胞與非MNA細胞相比有顯著的絲氨酸耗損，而MNA NB 細胞的核苷單磷酸酯則大量增加。此外，雙重壓制MTHFD2和PAICS與減少細胞增生、集落形成和遷移能力具有協同的作用，而不管是單一或是雙重壓制的SK-N-DZ細胞都減少了絲氨酸的消耗。當MTHFD2和PAICS皆被抑制時，AICAR的損耗進一步限制了GMP的產生，這意味著MYCN可能同時標的MTHFD2和PAICS以調節代謝反應。我們系統性地辨識到的MTHFD2和PAICS基因表現在十種細胞株中分別被anisomycin和apicidin顯著地抑制。與單獨使用anisomycin或apicidin相比，anisomycin和apicidin的雙重治療對抑制MNA NB細胞增生具有協同作用。探索基因調控和分子網絡或許能夠為臨床應用和生物性標靶的發現提供值得的資訊。 | zh_TW |
| dc.description.abstract | Multi-omics approaches have launched the era of cancer research that enhance our understanding of complex interactions in biological systems, aim to reveal the underlying molecular mechanisms, and identify therapeutic targets. We performed multi-dimensional proteomic approach by integrating the phosphoproteome and proteome to uncover functional networks in lung cancer. MCM2 serves as a licensing factor that facilitates DNA unwinding at the origin of DNA replication. However, the biological networks of MCM2 in lung cancer cells via protein phosphorylation remain unmapped. By applying omics technologies, we identified a total of 2361 phosphorylation sites on 753 phosphoproteins, and 4672 proteins, and found that the deregulation of MCM2 is involved in lung cancer cell proliferation, the cell cycle, and migration. Furthermore, HMGA1S99 phosphorylation was found to be differentially expressed under MCM2 perturbation in opposite directions, and plays a pivotal role in regulating lung cancer cell proliferation. This multi-dimensional proteomic approach, therefore enhances our capacity to therapeutically target cancer-specific phosphoproteins.
Amplification of MYCN is associated with tumor initiation and progression, and occurs in approximately 20% of all neuroblastoma (NB), while the underlying mechanism still remains elusive. In this study, we integrated MYCN-bound promoter regions using ChIP−seq and GEO profiles of NB patients; MTHFD2 and PAICS were differentially up-regulated with MYCN amplification (MNA), and also we revealed that MTHFD2 and PAICS are the target genes of MYCN with a positive correlation in both tissue samples and cell lines of NB. Targeted metabolomics was performed and found that the MNA NB cells had significant serine depletion while the levels of nucleoside monophosphates had massively elevated compared to non-MNA cells. Furthermore, the dual knock-down of MTHFD2 and PAICS had synergistic effect on diminishing the cell proliferation, colony formation and migration abilities, and also the consumption of serine was decreased in either the single or the double knock-down SK-N-DZ cells. As the abundance of both MTHFD2 and PAICS was suppressed, the AICAR levels depleted which further limited the production of GMP, suggesting MYCN might target MTHFD2 and PAICS simultaneously to regulate metabolic reaction. We systematically identified the gene expression of MTHFD2 and PAICS are significantly suppressed by anisomycin and apicidin across ten cell lines, respectively. The cotreatment of anisomycin and apicidin showed synergistic effects on the inhibition of MNA NB cell proliferation, as compared with either anisomycin or apicidin treatment alone. By exploring the gene regulation and molecular networks might be able to provide valuable information for clinical applications and biomarker discovery. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T03:13:26Z (GMT). No. of bitstreams: 1 ntu-107-D02b43001-1.pdf: 7111736 bytes, checksum: e2d20ae8eef1bddfbd6c48b3a62aabe1 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 口試委員會審定書…………………………………………………………………... I
ACKNOWLEDGEMENTS………………………………...…………………………II 中文摘要…………………………………...............................................……………V ABSTRACT…………………………………………………………......………….VII TABLE OF CONTENTS………………………………………………..……………IX LIST OF FIGURES…………………………………………………………….......XIV LIST OF TABLES………………………………………………………………..XVIII ABBREVIATION………………………….………………………………………XIX FOREWORD………………………………………………………………………XXI Chapter 1 Omics in Cancer Research……...…………………...………………………1 1.1 Introduction to Omics………………………………….…………………………1 1.2 Genomics and transcriptomics……………………………………………………2 1.3 Proteomics……………………………..…………………………………………4 1.4 Phosphoproteomics and metabolomics……………………………………….......6 1.5 Bioinformatics empowers multi-omics analysis in cancer……………………......8 Chapter 2 MCM2-regulated functional networks in lung cancer by multi- dimensional proteomic approach…………………………………................................9 2.1 Background……………………………………………………………………....9 2.1.1 Lung cancer……………………………………………………………........9 2.1.2 DNA replication…………………………………………………………....10 2.1.3 Protein Phosphorylation…………...………………………………………10 2.1.4 The MCM proteins…………………………………………………………11 2.2 Aims of study……………………………………………………………………13 2.3 Material and methods……………………………………………………………14 2.3.1 Analysis of TCGA data set…………………………...…………………….14 2.3.2 Cell lines and cell culture………………………………………………......14 2.3.3 Plasmid construction and DNA manipulation …………………..…………15 2.3.4 RNA interference…………………………………………………..………15 2.3.5 Sample preparation for phosphoproteome…………………………………16 2.3.6 Dimethyl labeling of peptides for phosphoproteome………………………17 2.3.7 Phosphopeptide enrichment…………………………………………..……18 2.3.8 NanoLC−MS/MS analysis for MCM2 phosphoproteome…........................19 2.3.9 Sample preparation for proteome…………………………………......……20 2.3.10 Isobaric tags for relative and absolute quantitation (iTRAQ) labeling..……21 2.3.11 Strong cation exchange (SCX) chromatography……………………...……22 2.3.12 Peptide desalting by ZipTip pipet tips………………………………...……22 2.3.13 NanoLC−MS/MS analysis for siMCM2 proteome …………………..……23 2.3.14 Phosphopeptide identification and phosphosite quantification……….……24 2.3.15 Protein identification and quantification…………………………..……….25 2.3.16 Functional annotation……………………………………………...………26 2.3.17 Cell proliferation assays……………………………………………………27 2.3.18 Cell cycle analysis…………………………………………………………27 2.3.19 Cell migration assays………………………………………………………28 2.3.20 Site-directed mutagenesis……………………………………………….....28 2.3.21 Immunoblot analysis…………………………………………………….....29 2.3.22 Statistical analysis………………………………………………………….30 2.3.23 Data availability……………………………………………………………30 2.4 Results…………………………………………………………………..………31 2.4.1 Overexpression of MCM2 correlates with poor survival rate in lung cancer patients……………....…………………………………………….…………………31 2.4.2 Quantitative phosphoproteome of lung cancer cells regulated by MCM2.…32 2.4.3 Quantitative proteome of lung cancer cells regulated by MCM2………..…33 2.4.4 Functional networks of MCM2-regulated proteins ……………………..…34 2.4.5 Validation of MCM2 functional networks on cell proliferation, cell cycles, and migration in lung cancer cells………………………………………………….…36 2.4.6 Identification of the MCM2-associated phosphoproteins……….................38 2.4.7 MCM2 regulates HMGA1 Ser99 in determining lung cancer cell viability...40 2.5 Discussion………………………………………………………………………42 Chapter 3 MYCN-mediated purine biosynthesis alters cancer metabolism via MTHFD2 and PAICS in neuroblastoma…………………………………………………………46 3.1. Background………………………………………………………………………46 3.1.1 MYCN in Neuroblastoma……………………………………………….....46 3.1.2 MYCN and metabolism……………………………………………………47 3.1.3 One carbon pool by folate and purine biosynthesis………………………...48 3.2 Aims of the study………………………………………………………………..50 3.3 Materials and methods………………………………………………………......52 3.3.1 Differential expression analysis…………………………………………....52 3.3.2 Public data sources and bioinformatics analysis……………………….......53 3.3.3 Cell culture………………………………………………………………...53 3.3.4 RNA isolation of neuroblastoma cells and patient tissues and cDNA synthesis ………………..........................................................……………………………54 3.3.5 Plasmid construction and DNA manipulation……………………………...55 3.3.6 RNA interference…………………………………………………………..55 3.3.7 qRT-PCR analysis………………………………………………………….56 3.3.8 Western blotting……………………………………………………………56 3.3.9 Luciferase reporter assay…………………………………………………..57 3.3.10 Generation of cell lines with stable knockdown of MTHFD2 and PAICS….58 3.3.11 Cell proliferation assays……………………………………………………58 3.3.12 Cell cycle analysis…………………………………………………………59 3.3.13 Cell migration assays………………………………………………………60 3.3.14 Cell harvest and extraction for targeted metabolomics assay………………60 3.3.15 Instrumentation, method development, and data analysis for targeted metabolism analysis…………………………………………………………………..61 3.3.16 Identification of potential compounds suppressing MTHFD2 or PAICS expression…………………………………………………………………………….62 3.3.17 Drug combination assay…………………………………………………....63 3.3.18 Statistical analysis……………………………………………………….....64 3.4 Results…………………………………………………………………………..65 3.4.1 Integrated analysis of multi-layer omics data reveals higher cellular metabolic activities in MNA neuroblastoma……………………………………….....65 3.4.2 MTHFD2 and PAICS expression are strongly correlated to MYCN status …………………………………………………………………....……………..67 3.4.3 MTHFD2 and PAICS are transcriptional targets of MYCN……………..…69 3.4.4 Synergistic effect of MTHFD2 and PAICS on the prognosis of neuroblastoma patients…………………………………………………………….…70 3.4.5 Dual knockdown of MTHFD2 and PAICS suppresses neuroblastoma cell growth and migration ability…………………………………………………..…71 3.4.6 MYCN-mediated metabolic enzymes MTHFD2 and PAICS participate in purine biosynthesis………………………………………………………………...…73 3.4.7 Knockdown of MTHFD2 and PAICS interrupts cell cycle at S phase in MNA neuroblastoma………………………………………………………………………75 3.4.8 Synergistic effect of combined treatment in MNA neuroblastoma…………76 3.5 Discussion………………………………………………………………………77 Chapter 4 Conclusions and future perspectives…………….........................................80 REFERENCES…………………………………………………………………….…84 FIGURES…...………………………………………………………………………101 TABLES…….………………………………………………………………………142 APPENDIX…………………………………………………………….…………...164 Publication List…...…………………………………………………………………164 | |
| dc.language.iso | en | |
| dc.subject | PAICS | zh_TW |
| dc.subject | 多體學 | zh_TW |
| dc.subject | 肺癌 | zh_TW |
| dc.subject | 神經母細胞瘤 | zh_TW |
| dc.subject | MCM2 | zh_TW |
| dc.subject | MYCN | zh_TW |
| dc.subject | MTHFD2 | zh_TW |
| dc.subject | MTHFD2 | en |
| dc.subject | Multi-omics | en |
| dc.subject | lung cancer | en |
| dc.subject | neuroblastoma | en |
| dc.subject | MCM2 | en |
| dc.subject | MYCN | en |
| dc.subject | PAICS | en |
| dc.title | 利用多種體學尋找癌症治療標的並探討其分子功能 | zh_TW |
| dc.title | Multi-omics approaches toward identifying therapeutic targets and understanding their molecular functions in cancer | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 黃宣誠(Hsuan-Cheng Huang),許家郎(Chia-Lang Hsu),王憶卿(Yi-Ching Wang),李岳倫(Alan Yueh-luen Lee),黃翠琴(Tsui-Chin Huang) | |
| dc.subject.keyword | 多體學,肺癌,神經母細胞瘤,MCM2,MYCN,MTHFD2,PAICS, | zh_TW |
| dc.subject.keyword | Multi-omics,lung cancer,neuroblastoma,MCM2,MYCN,MTHFD2,PAICS, | en |
| dc.relation.page | 164 | |
| dc.identifier.doi | 10.6342/NTU201801301 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-07-12 | |
| dc.contributor.author-college | 生命科學院 | zh_TW |
| dc.contributor.author-dept | 分子與細胞生物學研究所 | zh_TW |
| 顯示於系所單位： | 分子與細胞生物學研究所 | |
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