藉由大數據挖掘和全基因組識別建構基因與表觀遺傳網路並比較肺腺癌和肺鱗狀細胞癌之間的進展分子機制

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研究生：	張簡安 Chang, Chien-An
論文名稱：	藉由大數據挖掘和全基因組識別建構基因與表觀遺傳網路並比較肺腺癌和肺鱗狀細胞癌之間的進展分子機制 Investigating the Genome-wide Genetic and Epigenetic Networks for Comparing Progression Molecular Mechanisms between Lung Adenocarcinoma and Lung Squamous Cell Carcinoma via Big Data Mining and Genome-wide Identification
指導教授：	陳博現 Chen, Bor-Sen
口試委員:	王慧菁 Wang, Hui-Ching 詹鴻霖 Chan, Hong-Lin 蘇士哲 Sue, Shih-Che 王禹超 Wang, Yu-Chao
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2017
畢業學年度：	105
語文別：	英文
論文頁數：	102
中文關鍵詞：	肺腺癌、肺鱗狀細胞癌、非小細胞肺癌、基因與表觀遺傳網路、主成份網路投影方法、多分子藥物
外文關鍵詞：	lung adenocarcinoma, lung squamous cell carcinoma, NSCLC, genetic and epigenetic network, principal network projection (PNP), multi-molecule drug
相關次數：	點閱：3 下載：0
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肺癌是最常見的惡性腫瘤，是導致全世界癌症相關死亡人數最多的疾病。只有15.9％的肺癌患者存活5年以上。作為非小細胞肺癌（NSCLC）亞型的肺腺癌（LADC）和肺鱗狀細胞癌（LSCC）在全球中是肺癌的主要形式。由於其各自獨特的分子特徵，不同細胞的起源與不同的臨床反應，使它們被認為是不同的疾病。透過使用全基因組候選基因與表觀遺傳網路（GENs）、正常細胞與LADC和LSCC患者癌細胞的次世代定序(NGS)數據和DNA甲基化譜，並藉由系統識別方法，系統階層測定方法，以及利用蛋白質與蛋白質相互作用網絡（PPIN）與基因/ miRNA / lncRNA調控網絡（GRN）所建立的系統模型，和表觀遺傳網路，我們分別建立了LADC和LSCC在各自正常，早期，中期，以及晚期階段的基因與表觀遺傳網路。透過應用主成份網路投影方法（PNP），我們分別得到LADC和LSCC各自正常，前期，中期，以及晚期階段的核心GENs。為了比較LADC和LSCC之間基因和表觀遺傳機制，我們藉由比較LADC和LSCC各自的兩相鄰疾病階段間的核心GENs來萃取出差異的核心信號途徑。根據我們的結果，我們發現造成LADC和LSCC各自從正常階段到早期階段，早期階段到中期，中期到晚期階段的分子進展原因分別是由細菌感染（LPS），EGFR突變，miR-130b，miR-100HG和miR-1292的失調，E2F1泛素化，SFTPA2去泛素化和乙醯化，MYC和RB1的DNA甲基化; 缺氧環境，miR-30c2和miR-27b的失調，VIM，MYH9和ETS1的乙醯化，MDM4泛素化;過氧化氫導致的氧化壓力，miR-143HG和miR-19a的失調，ZEB1乙醯化，RHOB去乙醯化，PCK1的DNA甲基化; 暴露於尼古丁，miR-24-2和miR-1247的失調，以及lncRNA TUG1，KLF12泛素化和乙醯化，ERCC1泛素化和SHOX2的DNA甲基化;缺氧環境，HIF1A，IGF1和ETS1的乙醯化，ITGB1，TNS1，miR-21的DNA甲基化; NNK導致的氧化壓力，miR-9-2的失調，GATA3泛素化和去乙醯化，FOXL1去乙醯化，CDH3去泛素化，PDPN的DNA甲基化。最後，我們提出了六個基因和表觀遺傳多分子藥物，分別在LADC和LSCC各自的進展階段中標靶重要的生物標誌。

Lung cancer, the most common malignancy, results in the largest number of cancer-related deaths worldwide. Only 15.9% of lung cancer patients survive more than 5 years. Lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC), which are subtype of Non-small-cell lung cancer (NSCLC), are the predominant form of lung cancer in worldwide and they are thought to be distinct diseases due to their unique molecular characteristics, distinct cells of origin, and different clinical response. By using genome-wide candidate genetic and epigenetic networks (GENs), next-generation sequencing (NGS) data, and DNA methylation profiles of normal cells and cancer cells in LADC and LSCC patients, we respectively constructed GENs in normal , early , middle , and advanced stage of LADC and LSCC based on system identification method, system order detection scheme, and system modeling via protein-protein interaction networks (PPINs), gene/miRNA/lncRNA regulatory networks (GRNs), and epigenetic networks. Through applying principle network projection (PNP), we then identified the core GENs of LADC and LSCC in each stage from normal stage to advanced stage. To investigate and compare the progression genetic and epigenetic mechanisms between LADC and LSCC, we then extracted differential core signaling pathways by comparing core GENs between two connective stages of LADC and LSCC, respectively. Based on our results, we found that the progression from normal stage to early stage, early stage to middle stage, and middle stage to advanced stage LADC and LSCC are respectively caused by stimulation of bacteria infection (LPS), EGFR mutation, dysfunction of miR-130b, miR-100HG, and miR-1292, E2F1 ubiquitination, SFTPA2 deubiquitination and acetylation, DNA methylation of MYC and RB1; hypoxia, dysfunction of miR-30c2 and miR-27b, acetylation of VIM, MYH9, and ETS1, MDM4 ubiquitination; hydrogen peroxide induced oxidative stress, dysfunction of miR-143HG and miR-19a, ZEB1 acetylation, RHOB deacetylation, DNA methylation of PCK1; nicotine exposure, dysfunction of miR-24-2 and miR-1247, and lncRNA TUG1, KLF12 ubiquitination and acetylation, ERCC1 ubiquitination, and DNA methylation of SHOX2; hypoxia, acetylation of HIF1A, IGF1, and ETS1, DNA methylation of ITGB1, TNS1, miR-21; NNK induced oxidative stress, dysfunction of miR-9-2, GATA3 ubiquitination and deacetylation, FOXL1 deacetylation, CDH3 deubiquitination, DNA methylation of PDPN. Finally, we proposed six genetic and epigenetic multiple-molecule drugs to target significant biomarker in each progression stage LADC and LSCC, respectively.

Contents
誌謝        I
摘要        II
Abstract    III
Contents    IV
List of Tables    VIII
List of Figures    IX
Chapter 1.  Introduction    1
Chapter 2.  Materials and Methods    6
2.1    Overview of the construction for genome-wide GENS, core GENs, and core pathways of each progression stage in LADC and LSCC    6
2.2    Big data mining and data preprocessing of NGS data and methylation data for information of constructing GENs of human    7
2.3    Constructing genome-wide candidate GENs    8
2.4    Constructing stochastic regression models of candidate PPIN and candidate GRN of candidate GENs for LADC and LSCC    8
2.5    Parameter estimation of the stochastic regression models of candidate GENs via system identification method and system order detection    12
2.6    Extracting core GENs from the real GENs by using the PNP method    17
Chapter 3.  Results    22
3.1    Analysis of core pathways to investigate different progression genetic and epigenetic mechanisms of LADC and LSCC from normal stage to early stage    23
3.2    Analysis of core pathways to investigate different progression genetic and epigenetic mechanisms of LADC and LSCC from early stage to middle stage    25
3.3    Analysis of core pathways to investigate different progression genetic and epigenetic mechanisms of LADC and LSCC from middle stage to advanced stage    28
Chapter 4.  Discussion    33
4.1    Microenvironment change, dysregulation of miRNA/lncRNA regulation, DNA methylation, and epigenetic modification contribute to different progression genetic and epigenetic mechanisms from normal stage to progress to early stage of LADC and LSCC    33
4.1.1    Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from normal stage to early stage LADC    34
4.1.1.1    The inflammatory microenvironment caused by infection of bacteria can lead to dysregulation of EGFR and TLR4 signaling pathways to progress from normal stage to early stage LADC    34
4.1.1.2  Dysregulations of miR-130b, miR-100HG, and miR-1292, epigenetic modifications of EGFL7, SFTPA2, and E2F1, and DNA methylation of MYC and RB1, mutation of EGFR contribute to the progression from normal stage to early stage LADC    35
4.1.2  Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from normal stage to early stage LADC    37
4.1.2.1  The inflammatory microenvironment caused by exposure to nicotine can lead to the dysregulation of FGFR1, DDR1, CHRNA5 (α5 nAChR subunit) signaling pathways from normal stage to early stage of LSCC    37
4.1.2.2 Dysregulations of miR-24-2, miR-1247, epigenetic modifications of KLF12 and ERCC1, and DNA methylation of SHOX2 contribute to the progression from normal stage to early stage LSCC    39
4.2    Microenvironment change, dysregulation of miRNA/lncRNA regulation, DNA methylation, and epigenetic modification contribute to different progression genetic and epigenetic mechanisms from early stage to progress to middle stage of LADC and LSCC    40
4.2.1  Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from early stage to middle stage LADC    41
4.2.1.1 The hypoxic tumor microenvironment can lead to dysregulation of NOTCH1 and CD49d signaling pathways from early stage to middle stage LADC    41
4.2.1.2    Dysregulations of miR-30c-2 and miR-27b, epigenetic modifications of VIM, MYH9, MDM4, and ETS1 contribute to the progression from early stage to middle stage LADC    43
4.2.2  Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from early stage to middle stage LSCC    45
4.2.2.1  The hypoxic tumor microenvironment exposed to nicotine can lead to dysregulation of IGF-1R, TNS1, and ITGB1 (CD29) signaling pathways from early stage to middle stage LSCC    45
4.2.2.2  Dysregulation of miR106b, epigenetic modifications of HIF1α, IGF-1, and ETS1, and DNA methylation of ITGB1, TNS1, and miR21 contribute to the progression from early stage to middle stage LSCC    47
4.3  Microenvironment change, dysregulation of miRNA/lncRNA regulation, DNA methylation, and epigenetic modification contribute to different progression genetic and epigenetic mechanisms from middle stage to progress to advanced stage of LADC and LSCC    49
4.3.1  Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from early stage to middle stage LADC    50
4.3.1.1      The hydrogen peroxide secreted by cancer cells leads to the alteration of tumor microenvironment, causing dysregulation of EGFR, EPOR and ITGB1 (CD29) signaling pathways from middle stage to advanced stage of LADC    50
4.3.1.2      Dysregulations of miR-143HG and miR-19a, epigenetic modifications of ZEB1 and RHOB, and DNA methylation of PCK1 contribute to the progression from middle stage to advanced stage LADC    52
4.3.2  Dysfunctions of miRNA regulation, DNA methylation, epigenetic modification and microenvironment alteration contribute to the progression from middle stage to advanced stage LSCC    53
4.3.2.1  The oxidative stress induced by the stimulation of nicotine derived nitrosaminoketone (NNK) can potentially lead to the alteration of microenvironment, causing dysregulation of ERBB4, PDPN, and EMR2 signaling pathways from middle stage to advanced stage LSCC    53
4.3.2.2      Dysregulation of miR-9-2, epigenetic modifications of GATA3, FOXL1, and CDH3, and DNA methylation of PDPN contribute to the progression from middle stage to advanced stage LSCC    55
4.4  Discocery of genetic and epigenetic multiple drugs for treating early stage, middle stage, and advanced stage LADC and LSCC    57
Chapter 5.  Conclusion    63
Reference    91

List of Tables
Table 1.     The number of nodes and edges in candidate GENs    64
Table 2.     The number of identified nodes and edges of real GENs in each stage of LADC    65
Table 3.     The number of identified nodes and edges of real GENs in each stage of LSCC    66
Table 4.     Design of genetic and epigenetic multiple drug for the therapeutic treatment of early stage LADC    67
Table 5.     Design of genetic and epigenetic multiple drug for the therapeutic treatment of middle stage LADC    68
Table 6.     Design of genetic and epigenetic multiple drug for the therapeutic treatment of advanced stage LADC    69
Table 7.     Design of genetic and epigenetic multiple drug for the therapeutic treatment of early stage LSCC    70
Table 8.     Design of genetic and epigenetic multiple drug for the therapeutic treatment of middle stage LSCC    71
Table 9.     Design of genetic and epigenetic multiple drugs for the therapeutic treatment of advanced stage LSCC    72

List of Figures
Figure 1.     Flowchart of the construction for genome-wide GENS, core GENs, and core signaling pathways of each progression stage of LADC and LSCC and the discovery of potential genetic and epigenetic multiple drugs.    73
Figure 2.     The genetic and epigenetic networks (GENs) of normal stage, early stage, middle stage, and advanced stage LADC.    75
Figure 3.     The genetic and epigenetic networks (GENs) of normal stage, early stage, middle stage, and advanced stage LSCC.    76
Figure 4.     The core genetic and epigenetic network (GEN) of normal stage of lung cells near LADC cancer cells.    77
Figure 5.     The core genetic and epigenetic network (GEN) of early stage LADC.    78
Figure 6.     The core genetic and epigenetic network (GEN) of middle stage LADC.    79
Figure 7.     The core genetic and epigenetic network (GEN) of advanced stage LADC.    80
Figure 8.     The core genetic and epigenetic network (GEN) of normal stage of lung cells near LSCC cancer cells.    81
Figure 9.     The core genetic and epigenetic network (GEN) of early stage LSCC.    82
Figure 10.     The core genetic and epigenetic network (GEN) of middle stage LSCC.    83
Figure 11.     The core genetic and epigenetic network (GEN) of advanced stage LSCC.    84
Figure 12.     Core signaling pathways extracted from comparing genetic and epigenetic networks (GENs) between normal lung cells and early stage LADC and LSCC.    85
Figure 13.     Core signaling pathways extracted from comparing genetic and epigenetic networks (GENs) between early stage and middle stage LADC and LSCC.    86
Figure 14.     Core signaling pathways extracted from comparing genetic and epigenetic networks (GENs) between middle stage and advanced stage LADC and LSCC.    87
Figure 15. The specific core signaling pathways extracted from Figures 12-14 for investigating the differential progression molecular mechanisms between LADC and LSCC.    89
Figure 16.    Summarizing the differential progression genetic and epigenetic mechanisms from normal stage to early stage, early stage to middle stage, and middle stage to advanced stage LADC and LSCC.    90

                                

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