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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 莊曜宇(Eric Y. Chuang) | |
| dc.contributor.author | Tzu-Hao Lin | en |
| dc.contributor.author | 林資皓 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:00:33Z | - |
| dc.date.available | 2019-02-14 | |
| dc.date.copyright | 2019-02-14 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-02-12 | |
| dc.identifier.citation | 1. World Health Organization. Global Health Observatory. Geneva: World Health Organization who.int/gho/database/en/. 2018.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71428 | - |
| dc.description.abstract | 長片段非編碼核醣核酸(lncRNA)已知在許多生物體內的調控機制都有所影響，目前卻只了解極有限的長片段非編碼核醣核酸的調控目標基因。本篇研究中，我們利用一個新穎的方法，透過共表現分析(co-expression analysis)從基因表現的資料來鑑定出長片段編碼核醣核酸的目標基因；另外，藉由調控分析(modulation analysis)也可以得到腫瘤組織特有長片段非編碼核醣核酸與核醣核酸的配對關係。
本次研究採用的方法來自Modulated Gene Interaction Analysis，簡稱MAGIC，表現量資料經過前處理後，會根據MAGIC的三個部分進行計算：(1)計算長片段非編碼核醣核酸及核醣核酸之間的皮爾森相關係數(Pearson’s correlation coefficient)。(2)費雪轉換(Fisher transformation)。(3)費雪反轉換。調控分數(modulation score)會藉由以上方式被計算出來；同時，具有高調控分數的長片段非編碼核醣核酸及核醣核酸對亦被認為是在腫瘤組織中特有的基因對。本研究使用的基因表現量資料來自TCGA和GTEx兩個資料庫所提供的乳癌、大腸癌、肺癌及攝護腺癌資訊，每個癌症中特有的長片段非編碼核醣核酸及核醣核酸對會分別被鑑定出來。而根據計算出的目標基因，我們利用功能富集分析(functional enrichment analysis)來預測長片段非編碼核醣核酸可能參與的生物功能。 為了能更清楚地了解這些鑑定出的基因對的互動機制，我們預測基因對上潛在的轉錄因子鍵結位置(transcription factor binding site)，一個被相同轉錄因子鍵結的基因對，表示該長片段非編碼核醣核酸及核醣核酸是會被同一轉錄因子所調控。在乳癌中，MIAT—JAK3擁有共同的轉錄因子(SP1)；MIAT則可以被認為在乳癌發生中扮演重要的角色。而攝護腺癌中，FENDRR—HOXD10也共同被SP1調控，因此FENDRR在攝護腺癌中的目標基因及生物調控機制與HOXD10的關係是值得被考慮的。 | zh_TW |
| dc.description.abstract | Long non-coding RNAs (lncRNAs) are known for involving in various kinds of biological mechanisms. However, only limited target genes of lncRNA have been explored. In this study, we used a novel method to identify target genes of lncRNA from gene expression profiles using co-expression analysis. Furthermore, the tumor-tissue-specific lncRNA-mRNA association pairs were identified through modulation analysis.
The method is adapted from the previously method called “Modulated Gene Interaction Analysis (MAGIC). First, expression data passing the preprocessing procedures was applied to three steps of MAGIC: (1) Pearson’s correlation coefficient between lncRNAs and mRNAs, (2) Fisher transformation, and (3) Inverse Fisher transformation. Modulation score was introduced to identify cancer specific lncRNA target genes. lncRNA—mRNA pair with high modulation score was defined as tumor specific. The gene expression profiles included breast, colon, lung, and prostate cancers were obtained from TCGA and GTEx. The lncRNA-mRNA pairs for each cancer were identified respectively. Functional enrichment analysis was performed on lncRNAs to predict functions and involved pathways based on target genes of lncRNAs. To better understand the intra-interaction of the identified pairs, we predicted transcription factor binding sites on the pairs. A lncRNA—mRNA pair sharing a common transcription factor suggests that the transcription factor may regulate both the lncRNA and the mRNA, as well as SP1 within MIAT—JAK3 in breast cancer. This implied that MIAT has the potential to play a crucial role in breast cancer. In prostate cancer, FENDRR—HOXD10 was regulated by SP1. Thus, the target of FENDRR and regulation mechanism with HOXD10 in cancer are worth noted. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:00:33Z (GMT). No. of bitstreams: 1 ntu-108-R05945018-1.pdf: 3122325 bytes, checksum: 8cdda3a19311cb531bc286a3321185e7 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 致謝 I
中文摘要 II Abstract III List of Tables V List of Figures VI Chapter 1. Introduction 1 1.1 Cancers 1 1.2 Long non-coding RNA (lncRNA) 2 1.3 Co-expression analysis 3 1.4 Previous studies and motivation 5 Chapter 2. Materials and methods 7 2.1 Expression profiles 7 2.1.1 TCGA 7 2.1.2 GTEx 8 2.2 Preprocessing 8 2.3 Modulated gene interaction analysis (MAGIC) 9 2.4 Functional analysis 12 2.5 Survival analysis 14 2.6 Transcription factor binding sites prediction 14 Chapter 3. Results 16 3.1 Overview of identified lncRNA-mRNA pairs 16 3.2 lncRNA—mRNA pairs with high scores 18 3.3 Co-expression network and functional enrichment analysis 21 3.4 Transcription factor binding sites prediction on lncRNA—mRNA pairs 23 Chapter 4. Discussion 26 4.1 Potential interaction in BRCA 26 4.2 Potential interaction in PRAD 28 4.3 Limitations 29 Chapter 5. Conclusion 31 References 33 | |
| dc.language.iso | en | |
| dc.subject | 長片段非編碼核醣核酸 | zh_TW |
| dc.subject | 共表現分析網絡 | zh_TW |
| dc.subject | 癌症 | zh_TW |
| dc.subject | 基因對 | zh_TW |
| dc.subject | 目標基因 | zh_TW |
| dc.subject | lncRNA | en |
| dc.subject | co-expression network | en |
| dc.subject | cancer | en |
| dc.subject | gene pairs | en |
| dc.subject | target genes | en |
| dc.title | 鑑定癌症與正常組織間具共表現差異之蛋白質編碼與長片段非編碼核醣核酸對之交互關係 | zh_TW |
| dc.title | Identify Differential Tumor-specific Co-expression LncRNA-mRNA Pairs in Cancers | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 蕭自宏(Tzu-Hung Hsiao) | |
| dc.contributor.oralexamcommittee | 蔡孟勳(Mon-Hsun Tsai),賴亮全(Liang-Chuan Lai),盧子彬(Tzu-Pin Lu) | |
| dc.subject.keyword | 長片段非編碼核醣核酸,共表現分析網絡,癌症,基因對,目標基因, | zh_TW |
| dc.subject.keyword | lncRNA,co-expression network,cancer,gene pairs,target genes, | en |
| dc.relation.page | 58 | |
| dc.identifier.doi | 10.6342/NTU201900371 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-02-12 | |
| 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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