臺灣博碩士論文加值系統

本研究的目的是要探討表觀基因(表徵遺傳學; epigenetics)所調控的免疫監控低下，是否會影響兩種肺部疾病的發生–肺結核和肺癌。這兩種疾病的發生都是因為個體的免疫系統無法正常執行其功能，無法把結核菌或肺泡腫瘤細胞清除所致。表觀基因改變，例如去氧核醣核酸甲基化，在調控因應環境刺激(缺氧、毒物、感染)的免疫反應和基因表現上扮演關鍵的角色。因此，我們尋求能作為這兩種肺部疾病之早期診斷或預測治療反應的表觀基因所調控的免疫監控低下相關的生物標誌。第二型類鐸受器是人體對抗結核菌的固有免疫的主要調控者。在本研究第一部份，我們首先運用直接定序法，在184位肺結核及184位健康人的群體中，發現第二型類鐸受器基因多型性單倍型(-16934A/-15607G/-196 to -174 insertion /1350T)與活動性肺結核的罹病性有關。而且，肺結核病人帶有1350 CC、或GT repeats同質短對偶、或-196 to -174同質缺失基因型者，其血液自然殺手細胞數較高。接著，我們運用焦磷酸定序法、反轉錄多聚合脢反應法、流式細胞儀，檢測另外99位痰培養陽性肺結核病人並與77位健康人比較，發現其第二型類鐸受器基因啟動子去氧核醣核酸甲基化上升、第二型類鐸受器基因表現降低、血液單核球第二型類鐸受器蛋白質表現降低、血液自然殺手細胞第二型類鐸受器蛋白質表現上升、而且血清甲型腫瘤壞死因子/丙型干擾素濃度上升。大部份的這些生物標誌在六個月抗結核藥物治療後回到正常。在第二部份，我們首先分析30位非小細胞肺癌病人和20位健康人，週邊血液單核細胞基因表現全貌，發現末期肺癌病人的整體免疫反應趨向第二型幫助者細胞反應，尤其是第四型細胞介質傳導途徑隨著腫瘤進展和化學治療有明顯改變。反轉錄多聚合脢反應法確認了四個在肺癌病人表現上升(S100A15, DOK2)或下降(TLR7, TOP1MT)的基因，及六個在化學治療後表現上升(TLR7, CRISP3, TOP1MT)或下降(S100A15, DOK2, IL2RG)的基因。進一步在石蠟包埋的肺腫瘤作免疫組織化學分析，確認出S100A15的核染色在第四期病人比第三期明顯，而且在治療反應不佳的比治療反應好的明顯。接著，我們試圖找出S100A15基因啟動子去氧核醣核酸甲基化模式是否會影響該分子促進肺癌遠處轉移的作用。綜合起來看，本研究的結果讓我們對表觀基因所調控的免疫監控低下在這兩種肺部疾病的發生、診斷和治療上所扮演的角色有進一步的瞭解。

The purpose of this thesis research is to investigate epigenetic changes-mediated compromised immune surveillance that may affect the development of two common lung diseases, pulmonary tuberculosis (TB) and lung cancer. Both diseases develop when the individual’s immune system can not execute its normal function to eradicate either M.tb or tumor cell. Epigenetic changes, such as DNA methylation, play an essential role in regulating immune responses and gene expressions to environmental stimuli, such as hypoxia, toxin, and infection. Thus, we sough to identify epigenetic biomarkers for early diagnoses and predicting outcomes of both lung diseases. In the first part of this study, we found initially that one genetic haplotype (-16934A/-15607G/-196 to -174 insertion /1350T) of the toll-lke receptor 2 (TLR2) gene was linked to the susceptibility to active pulmonary TB disease in a cohort of 184 patients with pulmonary TB and 184 healthy controls, using direct sequencing. TB patients with the 1350 CC genotype, homozygous short alleles for GT repeats, or -196 to -174 deletion/deletion had higher blood natural killer (NK) cell counts. Then, we found higher DNA methylation levels over five CpG sites (3, 7, 9, 13, and 18) of the TLR2 promoter region, lower TLR2 gene expression, lower TLR2 protein expression on blood monocyte, higher TLR2 proein expression on blood NK cell, and higher serum TNF-α/IFN-γ levels in another cohort of 99 sputum culture positive pulmonary TB patients as compared to that in 77 healthy subjects, using pyrosequencing, RT-PCR, flowcytometry, and ELISA methods. Most of these biomarkers were reversed to normal after 6-month anti-TB treatment. In the second part, we initially analyzed whole genome microarray gene expression profiles of peripheral blood mononuclear cells from 30 patients with newly-diagnosed advanced stage non-small cell lung cancer (NSCLC), and 20 age-, sex-, and co-morbidity-matched healthy controls.We found the IL4 pathway significantly enriched in both tumor progression and chemotherapy signatures in patients with advanced NSCLC. Quantitative RT-PCR for the four up-regulated (S100A15, DOK2) and down-regulated (TLR7, TOP1MT) genes in the patients, and the six upregulated (TLR7, CRISP3, TOP1MT) and down-regulated (S100A15, DOK2, IL2RG) genes after chemotherapy confirmed the validity of the microarray results. Immunohistochemical analysis of the paraffin-embedded lung cancer tissues identified strong S100A15 nuclear staining not only in stage IV NSCLC as compared to stage IIIB NSCLC, but also in patients with stable or progressive disease as compared to those with a partial response. Then, we try to correlate aberrant DNA methylation patterns of the S100A15 promoter region with distant metastasis of lung adenocarcinoma. Taken together, results of this thesis research allow a better understanding of the effect of compromised immune surveillance on the development, diagnoses, and outcomes of both lung diseses through epigenetic regulations.

Table of Contents
指導教授推薦書 .……………………………………...……………..…
口試委員會審定書 ………………………………………………..........
誌 謝.... iii
中文摘要 iv
Abstract… vi
Table of Contents viii
DIRECTORY OF FIGURES xviii
DIRECTORY OF TABLES xxi
ABBREVIATION xxiv
DISCLAIMER xxvi
CHAPTER Ⅰ INTRODUCTION 1
1.1 Background 1
1.1.1 Toll-like receptor 2 (TLR2) genetic variants and its down-stream immune responses in patients with pulmonary tuberculosis (TB) 1
1.1.1.1 TLR2 genetic variants and pulmonary TB 1
1.1.1.2 Blood T cell counts and treatment response of
pulmonary TB 3
1.1.1.3 Serum IP-10 and IL-17 in patients with pulmonary
TB 4
1.1.2 Aberrant DNA methylation of the TLR2 promoter and pulmonary tuberculosis 6
1.1.3 Compromised immune surveillance in patients with non-small cell lung cancer (NSCLC) 7
1.1.4 Aberrant DNA methylation of the S100A15 promoter in
lung cancer 9
1.2 Purpose 10
1.2.1 To determine if TLR2 genetic polymorphisms, its down-stream cytokines, and T cell response are
associated with susceptibility or clinical phenotypes of pulmonary TB. 10
1.2.1.1 TLR2 genetic variants and pulmonary TB 11
1.2.1.2 Blood T cell counts and treatment response of
pulmonary TB 11
1.2.1.3 SerumIP-10 and IL-17 in patients with pulmonary
TB 12
1.2.2 To determine if TLR2 promoter methylation statuses are associated with the development and clinical phenotypes
of pulmonary TB 12
1.2.3 To determine which immunogenic biomarkers may serve
as predictors for treatment responses or prognosis of
NSCLC 13
1.2.4 To determine if S100A15 and DNA methylation statuses
of its promoter region are involved in the metastasis
potential of lung cancer 14
CHAPTER Ⅱ EXPERIMENTAL SETUP 16
2.1 Association studies of single nucleotide polymorphism (SNP)
of the TLR2 gene and its down-stream immune response in patients with active pulmonary TB 16
2.1.1 Subjects 16
2.1.1.1 TLR2 genetic variants and pulmonary TB 16
2.1.1.2 Blood T cell counts and treatment response of
pulmonary TB 17
2.1.1.3 Serum IP-10 and IL-17 in patients with pulmonary
TB 18
2.1.2 Methods 19
2.1.2.1 Molecular techniques and genotyping of TLR2 19
2.1.2.2 Determination of blood lymphocyte phenotypes 21
2.1.2.3 Processing of sputum samples for AFB smear and mycobacterial culture, CXR grading, and treatment course 21
2.1.2.5 Measurements of IP-10, IL-17, and CRP in the serum 23
2.2 Aberrant TLR2 promoter methylation and pulmonary TB 24
2.2.1 Subjects 24
2.2.2 Methods 25
2.2.2.1 Measurement of DNA methylation levels over TLR2 promoter region by bisulfite pyrosequencing method 25
2.2.2.2 Measurement of TLR2 mRNA gene expressions of peripheral blood leukocytes by quantitative realtime reverse transcription (RT)-PCR method 26
2.2.2.3 Measurement of TLR2 protein expressions on the cell surface of peripheral blood CD14Dmonocytes, CD3DCD56D NK T cell, CD3DCD56L T cell, and CD3LCD56DNK cells by flow cytometry 27
2.2.2.4 Measurement of TLR2 total protein expression of leukocytes by Western blot 28
2.2.3 statistical analysis 28
2.3 Compromised immune surveillance and lung cancer 29
2.3.1 Subjects 29
2.3.2 Methods 31
2.3.2.1 Processes of RNA Isolation and cRNA Synthesis 31
2.3.2.2 Microarray Data Analysis 32
2.3.2.3 Verification of Gene Expressions using TaqMan Quantification Real-time Reverse Transcriptase polymerase Chain Reaction (RT-PCR) 34
2.3.2.4 Immunohistochemistry (IHC) Staining of Lung
Cancer Tissues for S100A15 35
2.3.2.5 Evaluation of Immunohistochemical Staining for S100A15 36
2.3.3 Statistical analysis 36
2.4 Aberrant S100A15 promoter methylation and lung cancer 37
2.4.1 Subjects and materials 37
2.4.2 Methods 38
2.4.3 Statistical analysis 46
CHAPTER Ⅲ EXPERIMENT RESULTS 47
3.1 Association study of single nucleotide polymorphism (SNP)
of the TLR2 gene and its down-stream immune responses in patients with pulmonary TB 47
3.1.1 Demographic data of the subjects 47
3.1.1.1 TLR2 genetic variants and pulmonary TB 47
3.1.1.2 Blood T cell count and treatment response of
pulmonary TB 47
3.1.1.3 Serum IP-10 and IL-17 in patients with pulmonary TB 48
3.1.2 TLR2 genetic variants contribute to pulmonary TB 48
3.1.2.1 Allele and genotype frequencies in TB patients and healthy subjects 48
3.1.2.2 Association of TLR2 haplotype with pulmonary TB 49
3.1.2.3 Associations of the -196 to -174 Del/Del and 1350 CC genotype with TB phenotypes 50
3.1.2.4 Association between the TLR2 genotypes and blood absolute NK cell counts in TB patients 50
3.1.3 Blood T cell counts can predict treatment response of pulmonary TB 51
3.1.3.1 Association of blood absolute counts of lymphocyte subsets with treatment response 51
3.1.3.2 Multivariate analysis models and predictive accuracy 52
3.1.3.3 Long-term Outcomes 53
3.1.3.4 Drug-resistant TB 54
3.1.4 IP-10 and Il-17 can predict relapse risk and mortality 55
3.1.4.1 Higher serum IP-10 levels at month 2 in the HA group 55
3.1.4.2 Correlations of serum IP-10/hsCRP levels at diagnosis with disease severity 56
3.1.4.3 Lower serum IL-17 levels at month 2 in non-survivors 56
3.2 Aberrant TLR2 promoter methylation and pulmonary TB 57
3.2.1 Demographic data of the subjects 57
3.2.2 Aberrant TLR2 promoter methylation, and TLR2 gene/protein expressions in patients with active
pulmonary TB…. 58
3.2.2.1 Comparisons of TLR2 promoter methylation levels, TLR2 gene expression, and TLR2 protein expressions between TB patients and healthy subjects 58
3.2.2.2 Comparisons of TLR2 promoter DNA methylation
levels, TLR2 gene expression, and TLR2 protein expressions among various pulmonary TB phenotypes 60
3.2.2.3 Changes in TLR2 promoter DNA methylation levels, TLR2 gene expression, and TLR2 protein expressions after 6-month anti-TB treatment 61
3.3 Compromised immune surveillance and lung cancer 62
3.3.1 Demographic data of the subjects 62
3.3.2 Peripheral Immune Cell Gene Expression Changes in Advanced Non-Small Cell Lung Cancer Patients Treated with First Linen Combination Chemotherapy 62
3.3.2.1 Differentially Expressed Genes in PBMC Associated with Tumor Progression 62
3.3.2.2 Differentially Expressed Genes in PBMC after Combination Chemotherapy with CDDP and GEM in Cancer Patients 63
3.3.2.3 Interleukin 4 (IL4) Pathway 64
3.3.2.4 Distinct Expression Patterns Across Tumor Stages and Histopathological Subtypes 66
3.3.2.5 Confirmation of the Microarray Results using TaqMan Real-time RT-PCR 67
3.3.2.6 S100A15 Protein Expressions of Lung Cancer Tissues by IHC Staining for the Differentially Expressed Genes Associated with Tumor Progression and/or Chemotherapy Signatures 68
3.4 Aberrant S100A15 promoter methylation and lung cancer 70
3.4.1 Demographic data of the subjects 70
3.4.2 S100A15 nuclear accumulation is associated with high metastasis potential of lung adeonocarcinoma in clinical samples 70
3.4.3 S100A15 expression is increased in lung cancer cell lines with high metastasis potential 71
3.4.4 Aberrant DNA methylation of S100A15 promoter 71
CHAPTER Ⅳ DISCUSSION AND CONCLUSIONS 72
4.1 TLR2 genetic polymorphisms and its down-stream immune responses in patients with pulmonary TB 72
4.1.1 TLR2 genetic variants and pulmonary TB 72
4.1.1.1 Association of TLR2 haplotype with susceptibility to
TB 72
4.1.1.2 Association of TLR2 genetic variants with blood NK
cell counts 74
4.1.1.3 Conclusions for TLR2 genetic variants and
pulmonary TB 76
4.1.2 Blood absolute T cell counts can predict treatment
response of pulmonary TB 77
4.1.2.1 Independent factors for slow-responders afeter
2-month anti-TB treatment 77
4.1.2.2 Risk factors for relapsed pulmonary TB 78
4.1.2.3 Conclusions for blood T cell counts and treatment response 81
4.1.3 Serum IP-10 and IL-17 can predict relapse risk or
long-term outcomes after anti-TB treatment 82
4.1.3.1 Serum IP-10 can predict high risks of relapse after complete anti-TB treatment 82
4.1.3.2 Serum IL-17 can predict long-term mortality 84
4.1.3.3 Conclusions for serum IP-10/IL-17 and pulmonary TB 85
4.2 Aberrant TLR2 promoter methylation and pulmonary TB 86
4.2.1 TLR2 promoter hypermethylation is associated active pulmonary TB disease 86
4.2.2 Down-regulated TLR2 on monocyte but up-regulated
TLR2 on NK cell in patients with active pulmonary TB 87
4.2.3 Limitations 89
4.2.4 Conclusions 90
4.3 Compromised immune surveillance in patients with NSCLC 91
4.3.1 Immunosuppression with skewing to Th2-dominant
status in patients with advanced NSCLC 91
4.3.2 Increased S100A15 expression with tumor progression returned to normal after chemotherapy 94
4.3.3 Compromised Innate Immunity in advanced NSCLC
patients 96
4.3.4 Limitations 97
4.3.5 Conclusions 99
4.4 Aberrant S100A15 promoter methylation and NSCLC 99
4.4.1 Increased S100 A15 nuclear accumulation may predict a high metastasis potential of lung adenocarcinoma 99
4.4.2 Increased DNA methylation levels of 5 CpG sites in the S100A15 promoter region in the 3 lung cancer cell lines
with high metastasis properties 100
CHAPTER Ⅴ FUTURE PERSPECTIVE 101
Figures… 102
Tables….. 142
References 162
APPENDIX 192
Approval of human study (Institutional Review Board Approval) 193
Publication list 198
Research grants 203
CURRICULUM VITAE 204
Supplementary Tables of microarray gene expression profiles in
the lung cancer study 206
Table S1. Primer sequences and probe product number for assay quantitative real-time polymerase chain reactions used in
the present study. 206
Table S2. Selected microarray gene expression significantly
altered in peripheral blood mononuclear cells (PBMC) of advanced stage non-small cell lung cancer patients
compared with healthy subjects. 207
Table S3. Selected microarray gene expression significantly
altered in PBMC of advanced-stage non-small cell lung cancer patients after chemotherapy with cisplatin and gemcitabine compared with that before chemotherapy. 211
Table S4. Selected microarray gene expression significantly up-regulated in PBMC of advanced stage non-small cell
lung cancer patients with different stages and histopathologies in association with 1.5 fold change identified by unsupervised hierarchical clustering
analysis 216
Table S5. Raw data of immunohistochemical staining results
for S100A15. 221
Supplementary Figure 1. 222
Supplementary Figure 2. 223
口試委員審查意見回覆 224


DIRECTORY OF FIGURES
Fig. 1. Flow chart to show classification profiles.........................103
Fig. 2. Flow chart to show classification profiles........................104
Fig. 3. Diagrams showing pyrosequencing design, pyrograms, and protein blots of toll-like receptor 2...........105
Fig. 4. Linkage disequilibrium plots.......................................107
Fig. 5. Homozygous TLR2 -100 GT repeat polymorphism and absolute natural killer (NK) cell counts measured at diagnosis.................................108
Fig. 6. Homozygous TLR2 -196 to -174 Ins>Del polymorphism and absolute natural killer (NK) cell counts measured at diagnosis...................................109
Fig. 7. Homozygous TLR2 1350 T>C polymorphism and absolute natural killer (NK) cell counts measured at diagnosis..............110
Fig. 8. Relationships between blood absolute counts of T cell subsets, and 2-month response to anti-tuberculosis treatment in the study groups....................112
Fig. 9. Predictive accuracy of the T cell counts. ......................113
Fig. 10. Kaplan–Meier survival curves for 64 TB patients with separate lines according to age, and response to 2-month anti-tuberculosis treatment. ..........114
Fig. 11. Relationships between blood levels of IP-10, IL-17, and hsCRP, and risk of caviation and a positive sputum smear/culture after two months of anti-tuberculosis treatment in the study groups.........................................116
Fig. 12. Predictive accuracy of the serum IP-10 levels measured at month 2...117
Fig. 13. Relationships between blood levels of IP-10 and hsCRP at diagnosis, and disease activity. .................................................118
Fig. 14. Relationship between blood IL-17 levels measured at month 2 and all-cause mortality in the study population..........119
Fig. 15. Comparison of DNA methylation levels in the TLR2 gene promoter region..........120
Fig. 16. TLR2 gene/protein expressions of immune cells of the blood, and serum cytokine levels in pulmonary TB patients versus healthy subjects (HS)............121
Fig. 17. TLR2 promoter methylation levels, and TLR2 protein expressions on the blood immune cells in pulmonary TB patients of different clinical phenotypes..........123
Fig. 18. TLR2 promoter DNA methylation changes in the 25 TB patients before and after anti-TB treatment. The error bars show the 95% CI and mean...............125
Fig. 19. TLR2 gene/protein expression changes in the 25 TB patients before and after anti-TB treatment. .............................126
Fig. 20. The IL4 pathway was enriched in both tumor progression and chemotherapy signatures. ...................................................128
Fig. 21. Hierarchical clustering of PBMC samples from patients with advanced stage lung cancer and healthy controls. ............130
Fig. 22. Confirmation of microarray results with TaqMan real-time RT-PCR.........132
Fig. 23. Immunohistochemistry (IHC) staining for S100A15................134
Fig. 24. Survival curves based on tumor stages. ..............................137
Fig. 25. Nuclear S100A15 IHC staining in the 69 patients with lung adenocarcinoma...138
Fig. 26. S100A15 expressions in lung cancer cell lines.........................139
Fig.27. DNA methylation levels of the 5 CpG sites in the S100A15 promoter region with respect to the 4 lung cancer cell lines. ...140
Fig.28. Representative pyrograms of the 5 CpG sites in the S100A15 promoter region. ........................................................................141


DIRECTORY OF TABLES
Table 1. Biological characteristics of the genotyped TLR2 polymorphisms and the primers and conditions used for PCR .......................................143
Table 2. PCR amplification, pyrosequencing, and primers used in measuring DNA methylation and mRNA levels of the TLR2 gene ....................................144
Table 3. Characteristics of Study Participants...........................145
Table 4. Comparisons of clinical baseline characteristics between fast responders and slow responders to 2-month anti-TB treatment............................146
Table 5. Comparison of treatment medication and duration between fast responders and slow responders groups of patients with pulmonary tuberculosis .................148
Table 6. Comparison of the characteristics between high association (HA) and medium/low association (MA/LA) groups ............149
Table 7. Comparisons of outcomes between high risk (HA) and medium to low risk (MR/LR) groups with pulmonary tuberculosis ..............................150
Table 8. Allele frequencies of GT microsatellite repeat dinucleotides
polymorphism (a) in cases and control subjects.....................151
Table 9. Genotype and allele frequencies of TLR 2 gene polymorphisms in TB patients and control subjects* ............152
Table 10. Estimation of TLR2 haplotype frequencies in the study population by using the expectation-maximization algorithm with the Haploview software ...........153
Table 11. Association of TLR2 -196 to -174 deletion/deletion and 1350 CC genotypes with TB phenotypes. Odds ratio (OR) and 95% confidence interval (CI) are reported when the common allele (insertion or T) is dominant. ..........................154
Table 12. Cox proportional hazard model to analyze predictors for mortality in all the patients with pulmonary tuberculosis ......155
Table 13. Demographic and clinical characteristics of culture positive pulmonary tuberculosis (TB) patients and healthy subjects ........................156
Table 14. Comparison of methylation levels over the 20 CpG sites in the toll-like receptor 2 promoter region between pulmonary TB patients and healthy subjects....157
Table 15. Baseline and clinical characteristics of the 30 advanced stage non-small cell lung cancer patients and 20 matched healthy controls.......................158
Table 16. IL4 pathway-associated genes that were differentially expressed with tumor progression and / or chemotherapy.....159
Table 17. Use of Cox proportional hazard model to analyze predictors for 3-year overall mortality in the 26 non-small cell lung cancer patients ................160
Table 18. Immunohistochemistry staining of lung cancer tissues compared with normal lung tissues published in the Human Protein Atlas website* for the differentially expressed genes identified in this study associated with tumor progression and/or chemotherapy signatures * www.proteinatlas.com .................................161

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