臺灣博碩士論文加值系統

在廣泛性的流行病學及分子研究已發現外生殖器感染特定高危險性的人類乳突病毒與子宮頸皮內腫瘤及子宮頸癌有很強的關聯性。目前，人類乳突病毒偵測已在一些臨床應用上扮演輔助的角色；例如：atypical squamous cells of undetermined significance (ASCUS) 的處置，與細胞學偵測子宮頸癌及子宮頸皮內腫瘤的篩檢及追蹤。在這個研究中，我連續分析2,154位已接受子宮頸圓錐切片的病人，在挑除圓錐切片中診斷為子宮頸癌或輕度子宮頸皮內腫瘤(Cervical Intraepithelial Neoplasia I)者、圓錐切片後十二週內切除子宮者及無追蹤資料者後，只剩765位病人被納入分析。其中有279位是圓錐切片邊緣或子宮內頸有殘餘病變者(A組)而486位是兩處皆無病變者(B組)。三年的累積殘餘或復發重度子宮頸病變率為10.3%。結果顯示人類乳突病毒的情形、圓錐切片邊緣及細胞學皆為對殘餘或復發重度子宮頸病變的有意義預測因子。一再顯示人類乳突病毒檢查對於病人之追蹤有實用價值，更有助於我們對重度子宮頸病變圓錐切片後的自然史的暸解。
為了去暸解子宮頸癌不同臨床組織分型的分子機制，我們分析了子宮頸癌上皮細胞癌、腺癌及混合型上皮細胞/腺癌的基因表現。在實驗設計方面，將接受根治性子宮切除的子宮頸癌病人納入研究對象。在手術中將部分子宮頸癌組織及相對應的正常組織收集、萃取RNA並利用cDNA微陣列作分析，再利用即時定量聚合連鎖反應(Real-time Quantitative PCR)檢測有統計意義的基因。在腺癌中有明顯上升表現的基因有carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5)、tumor-associated calcium signal transducer 1 (TACSTD1)、S100 calcium binding protein P (S100P)、mesothelin (MSLN)。在上皮細胞癌中，S100 calcium binding protein A9 (S100A9)及annexin A8 (ANXA8)基因有明顯上升表現。最後再用獨立的交叉比對方式回溯檢驗63位已知預後的病人，檢驗結果顯示這六個基因與組織分類是有統計意義的；多變量迴歸分析顯示CEACAM5及TACSTD1有預測預後之能力。結論是綜合cDNA微陣列分析、即時定量聚合連鎖反應及免疫染色可區分出子宮頸癌上皮細胞癌、腺癌的分子形貌，而TACSTD1有當做預後因子的潛力。
為了探討子宮頸癌病人接受治療時發生的轉錄反應，我也分析了巨大型第一期B至第四期子宮頸上皮細胞癌病人接受複合性化學放射治療之週邊血液的連續基因變化。在未接受治療、治療開始一週、治療完成後一週及治療後一個月的四個時間點抽取週邊血並使用DNA微陣列分析。有意義上升的53個基因被認出來之後，以階層式群聚法分類(hierarchical clustering)可分為二組。第一組有9個基因包含了S100A9，第二組在骨髓被最嚴重抑制時有44個基因表現上升。第二群中，胎兒及胚胎血紅素基因(HBG2及HBZ)隨同成人血紅素基因(HBA2及HBB)，紅血球的同位酶[carbonic anhydrase I (CA1)]及製造紅血球的基因[aminolevulinate, delta-, synthase 2 (ALAS2)]都有表現。與癌症相關的基因如cathepsin D (CTSD)及activin A receptor, type I (ACVR1)也在貧血時上升。Immunoglobulin kappa variable 1D-13 (IGKV1D-13)在血液毒性指標為Ⅲ/Ⅳ者會明顯下降。因此，血紅素下降會導致紅血球製造酶及與癌症相關的基因上升表現，IGKV1D-13也許可做為子宮頸癌接受複合性治療的毒性副作用指標。

Extensive epidemiologic and molecular research has strongly linked anogenital infection of certain human papillomaviruses (HPVs) to the development of cervical neoplasia and cervical cancer. Currently, HPV DNA detection has played a triage role in the management of atypical squamous cells of undetermined significance (ASCUS), primary screening with cytology for the detection of cervical cancer and cervical intraepithelial neoplasia (CIN), and follow-up in a variety of clinical settings. In this study, I analyzed consecutively a series of 2,154 patients undergoing conization of the cervix. Patients who were diagnosed with cervical cancer or CIN 1, had a hysterectomy within 12 weeks after conization, or had no follow-up data were excluded. The remaining 765 patients were analyzed. Of the 765 patients, 279 had dysplasia at the margins of the conization or endocervix (group A) while 486 were free of neoplasia at both the margins and endocervix (group B). The 3-year cumulative rate of residual/recurrent high-grade CIN was 10.3%. Our results indicated that HPV follow-up status, margin status and follow-up cervical cytology were significant predictors for residual/recurrent high-grade CIN. This study suggested that HPV DNA testing is useful in the follow-up of these patients and in the understanding of the natural history after conization for high-grade CIN.
In a parallel attempt to understand molecular mechanisms for the different clinical features between adenocarcinoma/adenosquamous carcinoma (AC/ASC) and squamous carcinoma (SC) of the uterine cervix, I analyzed gene expression profiles of different histological subtypes of cervical cancer. Cancer specimens and surrounding normal tissue counterparts were separately collected from cervical cancer patients undergoing type III radical hysterectomies. DNA microarray analyses indicated that genes including carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), tumor-associated calcium signal transducer 1 (TACSTD1), S100 calcium binding protein P (S100P), and mesothelin (MSLN), were upregulated in AC. Contrarily, genes involved in the epidermal differentiation complex, such as S100 calcium binding protein A9 (S100A9) and annexin A8 (ANXA8), were upregulated in SC. Cross-validation of the results using an independent comparable group of patients with known long-term outcomes showed that the correlation between the six selected differentially-expressed genes and histology was highly significant. Furthermore, using a multivariate Cox proportional hazards regression analysis, I found CEACAM5 and TACSTD1 to be highly significant prognostic factors. The combination of cDNA microarray, RTQ-PCR, and immunohistochemical results of this study has clearly defined different gene profiles for AC and SC. Moreover, TACSTD1 expression may be a novel prognostic factor for poor outcome.
To investigate patient responses to cancer treatment at the transcriptional level, I analyzed serial changes of gene expression profiles in peripheral blood of cervical cancer patients (bulky stage IB –IVA squamous cell carcinomas) undergoing concurrent chemoradiation (CCRT). Total RNAs at four time points (before CCRT treatment, one week after the first course of chemotherapy, one week and one month after the completion of CCRT) were analyzed using DNA microarray. Fifty-three genes that were significantly overexpressed during CCRT were categorized into two groups by hierarchical clustering. Group 1, consisting of nine genes including S100A9, was upregulated during CCRT. Group 2 (44 genes) was upregulated after treatment during which patients had been severely myelosuppressed. In Group 2, fetal and embryonic hemoglobin genes (HBG2 and HBZ) along with adult hemoglobin genes (HBA2 and HBB), red blood cells isozyme [carbonic anhydrase I (CA1)], and enzymes involved in heme biosynthesis [aminolevulinate, delta-, synthase 2 (ALAS2)] were overexpressed. Cancer-related genes, cathepsin D (CTSD) and activin A receptor, type I (ACVR1) were significantly upregulated in anemic patients in CCRT. Immunoglobulin kappa variable 1D-13 (IGKV1D-13) was significantly downregulated in patients with grade 3/4 hematologic toxicity. Therefore, declining hemoglobin may reactivate fetal and embryonic hemoglobin genes as well as the enzymatic activities of erythrocytes and cancer-related genes in cervical cancer patients during CCRT. Our results suggested that the downregulation of IGKV1D-13 may predict hematologic toxicity in cervical cancer patients during CCRT.

TABLE OF CONTENTS
指導教授推薦書
論文口試委員會審定書
授權書………………………………………………………………………………iii
誌謝…………………………………………………………………………………v
中文摘要……………………………………………………………………………vii
英文摘要……………………………………………………………………………viii
PART I. 8
1. CERVICAL NEOPLASIA 9
1.1. Classification of preinvasive cervical disease 9
1.1.1. The Dysplasia Terminology 9
1.1.2. Cervical Intraepithelial Neoplasia 9
1.1.3. The Bethesda System 9
1.2. Molecular Biology of Cervical Neoplasia 10
1.2.1. Human Papillomaviruses: Taxonomy and Biology 10
1.2.2. Human Papillomavirus Type-Specific Disease Pattern 14
1.2.3. How HPV Infections Lead to Cervical Neoplasia 16
1.2.4. Cofactor Interaction with Human Papillomavirus 17
1.2.4.1. Cigarette smoking 17
1.2.4.2. Other microbial agents 18
1.2.4.3. Sex hormonal influences 18
1.2.4.4. Immunosuppression 18
1.2.5. HPV DNA Detection 18
1.2.5.1. HPV Hybrid Capture Assay 18
1.2.5.2. HPV DNA Assays: Direct hybridization 20
1.2.5.3. HPV DNA Assays: Amplification (PCR) 20
1.2.5.4. HPV Blot (PCR-based genechip) 21
1.2.6. Application of HPV Testings 29
1.2.6.1. In primary screening 29
1.2.6.2. In the triage of minor cytologic abnormalities 29
1.2.6.2. Prognostic role of genotyping in invasive cancer 30
1.2.7. Common Non-human Papillomavirus Disturbances Found in Cervical Cancers 39
1.2.7.1. Chromosomal abnormalities 39
1.2.7.2. Signal transduction modulators in cervical cancer 40
1.2.7.3. Angiogenesis modulation 40
1.3. Epidemiology of Cervical Cancer in Taiwan 40
1.4. Screening and Diagnosis of Cervical Neoplasm 40
1.4.1. Systematic Approach to Colposcopy 42
1.5. Classification and Staging of Cervical Cancer 42
1.5.1. Squamous Cell Carcinoma 42
1.5.2. Adenocarcinoma and Adenosquamous Carcinoma 42
1.5.3. Other Cell Types 44
1.6. Management of Cervical Dysplasia and Cervical Cancer 46
1.6.1. Cervical Intraepithelial Neoplasia 46
1.6.1.1. Cold-knife conization 47
1.6.1.2. Loop Electrosurgical Excision (LEEP) 47
1.6.1.3. Hysterectomy 47
1.6.2. Microinvasive Cervical Cancer 48
1.6.2.1. Stage IA1 cervical carcinoma 48
1.6.2.2. Stage IA2 cervical carcinoma 49
1.6.3. Early-Stage Cervical Cancer (Stage IB1 and Early Stage IIA Cancer) 49
1.6.4. Treatment of Recurrent Cervical Cancer 49
1.6.5. Posttreatment Surveillance 50
1.7. Special Consideration: Locally Advanced Cervical Cancer 51
1.7.1. Concurrent Chemoradiation (CCRT) 51
1.7.2. Hemoglobin Level and Anemia in CCRT 52
1.7.2.1. Normal hemoglobin, blood cells and hemopoiesis 52
1.7.2.2. Reactivation of fetal and embryonic hemoglobin genes 52
1.7.3. Impact of Anemia and Tumor Hypoxia in CCRT 53
2. MICROARRAYS IN THE POST-GENOMIC ERA 55
2.1. Introduction 55
2.1.1. The Making of Microarrays 55
2.1.2. The Use of Microarrays 55
2.2. Microarray Bioinformatics 60
2.2.1. Computer Design of Oligonucleotide Probes 60
2.2.2. Design of Microarray Expression Experiments 60
2.2.2.1. Choice of technology and arrangement of samples. 60
2.2.3. Sequence Databases for Microarrays 63
2.2.3.1. Primary sequence databases 63
2.2.3.2. Secondary sequence databases 66
2.2.4. Image Analysis 66
2.2.5. Normalization 67
2.2.5.1. Data cleaning and transformation 67
2.2.5.2. Within-array normalization 67
2.2.5.3. Between-Array normalization 68
2.2.6. Analytical Methods 69
2.2.6.1. Hierarchical clustering 69
2.2.6.2. Self-organized map (SOM) and K-means clustering 69
2.2.6.3. Principal-components analysis (PCA) 69
2.2.6.4. Nearest neighbors 70
2.2.7. Laboratory Information Management System (LIMS), Databases, and Data Management 70
2.2.8. Minimal Information About A Microarray Experiment (MIAME) 70
2.2.9. Ontologies 71
2.3. Target Preparation 71
2.3.1. RNA Preparation from Tissues 71
2.3.2. RNA Preparation from Whole Blood 72
3. VERIFICATION OF MICROARRAY RESULTS: SINGLE-GENE ANALYSES 76
3.1. Real-Time Quantitative PCR (RT-QPCR) 76
3.1.1. Analysis of Relative Gene Expression Data using the 2-ΔΔCT Method 77
3.1.2. Statistical Analysis of RT-QPCR Data 78
4. MICROARRAYS AND CANCER 79
4.1. Applications of DNA Microarrays to the Management of Cancer Patients 79
4.2. Gene Expression in Cervical Cancer 80
4.2.1. Implications from Cervical Cancer Cell Lines 80
4.2.1.1. Different cell lines have different gene expressions 80
4.2.1.2. Transforming growth factor-beta 1 81
4.2.1.3. In vitro radiation 82
4.2.2. Differentiation between Malignant and Normal Cervical Epithelia 83
4.2.3. Pattern Distinction between Different Cell Types and Biomarker Discovery of Aggressive Cancer 84
4.2.4. Association of Expression Profiling with Radiation 85
5. LITERATURE CITED IN PART I 88
PART II 111
1. KNOWLEDGE GAPS TO BE FILLED 112
2. OBJECTIVES 112
PART III 113
1. ABSTRACT 114
2. INTRODUCTION 114
3. MATERIALS AND METHODS 115
3.1. Trial Profile 115
3.2. Conization Procedures 116
3.3. Human papillomavirus testing 118
3.4. Clinical Correlation and Statistical Analyses 118
4. RESULTS 119
4.1. Trial Profile 119
4.2. Correlation of Histopathological Findings (Positive margin or endocervix) with Cytology and HPV Testings 119
4.3. Correlation of Histopathological Findings (Negative margin or endocervix) with Cytology and HPV Testings 120
4.4. Cumulative Rates of Recurrent/Residual High-grade Cervical Intraepithelial Neoplasia 120
4.5. Correlation of Human Papillomavirus Follow-up Status and Abnormal Cytology 124
5. DISCUSSION 126
6. LITERATURE CITED IN PART III 129
PART IV 131
1. ABSTRACT 132
2. INTRODUCTION 133
3. MATERIALS AND METHODS 133
3.1. Cervical Cancer and Normal Tissues 133
3.2. Preparation of RNA 134
3.3. Microarray Preparation 134
3.4. Microarray Data Analysis 135
3.5. Real-Time Quantitative PCR (RTQ-PCR) 135
3.6. Immunohistochemistry 135
3.8. Survival Analysis 137
4. RESULTS 137
4.1. Patient Demographics 137
4.2. Clustering of Highly-Expressed Genes and Identification of Candidate Genes in Adenocarcinoma and Squamous Cell Carcinoma 138
4.3. Validation of Microarray Data by RTQ–PCR 138
4.4. Verification of Selected Candidate Tumor Markers by Immunohistochemistry 144
4.5. Correlation of Gene Expression Profile and Immunohistochemistry on Selected Candidate Tumor Markers in Adenosquamous Carcinoma 144
4.6. Statistical analysis of the clinical association of the selected IHC expression patterns 149
5. DISCUSSION 149
6. LITERATURE CITED IN PART IV 158
PART V 161
1. ABSTRACT 162
2. INTRODUCTION 163
3. MATERIAL AND METHODS 164
3.1. Patient Enrollment and Healthy Controls 164
3.2. Concurrent Chemoradiation 164
3.3. Collection of Peripheral Venous Blood and Sample Preparation 165
3.4. Design and Procedures of Microarray Experiments 165
3.5. Data Analysis 166
3.6. Real-Time Quantitative PCR (RT-QPCR) 166
3.7. Correlation of the Gene Expression Profiles with Clinical Course of Patients 167
3.8. Toxicity 167
4. RESULTS 167
4.1. Patient and Control Characteristics 167
4.2. Global Gene Expression Variations among the Normal Control and the Four Time Points in Cancer Patients 167
4.3. Categorization of Differentially-expressed Genes into Two Distinct Groups 170
4.4. Classification of Genes with Gene Ontology (GO) 170
4.5. Activation of Fetal and Embryonic Hemoglobin Genes 175
4.6. Increased Enzymatic Expressions Parallel to Those of Fetal and Embryonic Hemoglobin Genes during CCRT 175
4.7. Changes of Gene Expression in Cancer-related Genes 175
4.8. Verification of Genes by RT-QPCR 177
4.9. Patient Outcome 177
4.10. Toxicity 177
5. DISCUSSION 180
6. LITERATURE CITED IN PART V 184
PART VI. 187
1. HUMAN PAPILLOMAVIRUS INFECTION IS THE CAUSATIVE AGENT FOR CERVICAL INTRAEPITHELIAL NEOPLASIA AND CERVICAL CANCER 188
2. HIGH-GRADE CERVICAL INTRAEPITHELIAL NEOPLASIA IS TREATED MAINLY BY CONIZATION 189
3. FOLLOW-UP OF HUMAN PAPILLOMAVIRUS INFECTION IN POSTCONIZATION 190
4. MOLECULAR PROGNOSTIC FACTORS OBTAINED FROM MICROARRARY ANALYSES 191
5. GENE EXPRESSIONS IN EARLY BULKY AND ADVANCED CERVICAL CANCER UNDERGOING CONCURRENT CHEMORADIATION 192
6. DIRECTIONS OF FUTURE RESEARCH 193
6.1. Role of human papillomavirus infections in lymphoepithelioma-like carcinoma of the cervix 193
6.2. Human Papillomavirus Status and Follow-up of Patients after Hysterectomy 195
6.3. Integrated Analyses of MicroRNA, mRNA Gene Expression, and Genomic Variations in Gynecologic Cancers 196
7. LITERATURE CITED IN PART VI 199
LIST OF ABBREVIATIONS 204
LIST OF FIGURES 206
LIST OF TABLES 208
VITA 210

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