臺灣博碩士論文加值系統

Ovarian cancer (OC) is basically a heterogeneous disease with different chemo-sensitivity and distinct molecular alternations for each histological subtype. The relative frequencies of subtypes were urgent for designation of clinical trial. Germline BRCA1 or BRCA2 mutations and other cancer-predisposition genes, which are related to hereditary breast-ovarian cancer (HBOC), contributes to some OC patients. The clinical genotype-phenotype information of Taiwan HBOC have not been well studied. After exploring literatures and our hospital cohort, we found that relative frequencies of subtypes were not homogenous across countries. We also analyzed genetic mutations in HBOC patients in our hospital between 2011 and 2016 and other Taiwan publications. The prevalence of germline BRCA1, BRCA2 and non-BRCA1/2 pathogenic mutations was 7.7% (21/272), 6.8% (16/236) and 8.2% (13/159), respectively among 272 HBOC patients. The main pathogenic/likely pathogenic mutations in non-BRCA1/2 genes included ATM, BRIP1, FANCI, MSH2, MUYTH, RAD50, RAD51C and TP53. The interplay between molecular variations in tumor microenvironment and OC chemoresistance remains unclear. By analyzing public available microarray datasets, we found that periostin (POSTN) was overexpressed in cancer stroma in OC patients. Overexpression of stromal POSTN is a significantly independent poor prognostic predictor for OC patients in immunohistochemistry analysis. Patients with high levels of stromal POSTN tend to have higher percentage of cisplatin resistance and POSTN tumor microenvironment can induce cisplatin resistant and activate AKT pathway.

卵巢癌是一種複雜的疾病，不同的病理分型有著不同的基因分型與不同化療藥物的感受性. 對於設計人體試驗藥物應用，探討不同種族好發的卵巢癌類型與遺傳基因型是很重要的，卵巢癌分成許多種型別，每個國家好發的比例可能不同；其中有些病患是屬於「遺傳性乳癌卵巢癌症候群」（Hereditary Breast and Ovarian Cancer， 簡稱HBOC），主要是由乳癌基因BRCA1和BRCA2發生突變所致。臺灣的HBOC基因型-表徵型的研究也需要更多的研究。本研究收集台北榮總卵巢癌病患與大規模文獻搜尋整理，發現不同種族好發的上皮性卵巢癌類型確有不同。本研究也收集在台北榮總病患中疑似「遺傳性乳癌卵巢癌症候群」與基因型結果，聯合其他台灣文獻，總共統計272病患中發現結果發現約有7.7% 的病患帶有BRCA1突變，6.8%帶有BRCA2突變和8.2%帶有其他相關的基因突變，其他與遺傳癌症相關基因還有包含ATM, BRIP1, FANCI.,MSH2, NUYTH, RAD50, RAD51C,TP53。除了探討卵巢癌的不同分型的分布與遺傳性基因的關係，腫瘤微環境與卵巢癌化療抗藥性之間的關聯值得探討。我們透過病人組織檢體染色和生物資料庫發現，腫瘤間質(stroma)內的骨膜素表現越高者，卵巢癌的預後越差。骨膜素(periostin)，屬於細胞基質外蛋白質，過去被發現與ㄧ些癌症預後相關。爾後透過分析抗藥性的資料，也發現與骨膜素表現越高者，將來發生鉑金類抗藥性的比例越高。進ㄧ步分析發現微環境骨膜素蛋白質，可透過活化AKT路徑增加卵巢癌細胞中的抗藥性。若合併使用AKT 抑制劑，可以克服因為骨膜素誘發的卵巢癌抗藥性。結果有機會幫助於因骨膜素高者合併抗藥性的卵巢癌病患的臨床用藥開發。

致謝 i
目錄 ii
English Abstract vii
中文摘要 viii
List of abbreviations ix
1.0 Introduction 1
1.1 The diversity of ovarian cancer (OC) 1
1.2 The genetic mutation in Taiwan hereditary breast and ovarian cancer (HBOC) patients 1
1.3 The genetic contribution in ovarian cancer chemo-resistance 3
2.0 Rationale and Research plan 4
2.1 Project 1: The study of OC subtype distribution 4
2.2 Project 2: The frequency of genetic mutations in Taiwan HBOC 4
2.3 Project 3: Discover new biomarkers for OC chemo-resistance 4
3.0 Material and methods 5
3.1 The study of OC subtype distribution 5
3.1.1 Database retrieva 5
3.1.2 Search strategy of systematic reviews 5
3.1.3 Inclusion and exclusion criteria- 5
3.1.4 Screening and data extraction 5
3.1.5 Assessment of methodological quality 6
3.1.6 Statistical analysis 6
3.2: The frequency of genetic mutations in Taiwan HBOC 7
3.2.1 Study population-Hospital cohort 7
3.2.2 Mutation screening 8
3.2.2.1 BRCA1/2: Re-sequencing array (BRCAchip) 8
3.2.2.2 Multi-gene panel test: Library construction, target region capture, and massively parallel sequencing 9
3.2.3 Mutational analysis and web-server prediction programs (in silico bioinformatic analysis) 9
3.2.4 Literature search strategy and meta-analysis 10
3.3 Discover new biomarkers for OC chemo-resistance 11
3.3.1 Gene expression analysis of tumor for chemotherapy response in OC 11
3.3.2 Patients’ samples collections 12
3.3.3 Tissue array construction 13
3.3.4 Immunohistochemistry 14
3.3.5 Cell line, chemicals and reagents 14
3.3.6 Analysis of high-grade ovarian serous cystadenocarcinoma in The Cancer Genome Atlas (TCGA) 15
3.3.7 Cell proliferation assay 15
3.3.8 Western blotting analysis 15
3.3.9 Statistical analysis 15
4.0 RESULTS
4.1 The study of OC subtype distribution 17
4.1.1 Database analysis and quality 17
4.1.2 The distribution of each subtype 17
4.1.3 The distribution pattern of subtypes 18
4.2 The frequency of genetic mutations in Taiwan HBOC-- 29
4.2.1 Distribution of variations in BRCA1/2 and other non-BRCA genes 18
4.2.2 Prevalence of pathogenic BRCA1/2 and non-BRCA mutations in HBOC patients 19
4.2.3 Mutation rate in populations with different family histories, ages at diagnosis, and personal histories 19
4.3 Discover new biomarkers for OC chemo-resistance: Periostin (POSTN) 20
4.3.1 Identification of up-regulated POSTN in ovarian cancer stroma 20
4.3.2 Association of POSTN expression in cancer stroma with late stage OC 20
4.3.3 Stronger association of POSTN expression in cancer stroma and poor prognosis 21
4.3.4 POSTN induces cisplatin resistance in A2780 cells through AKT activation 22
5.0 Discussion
5.1The study of OC subtype distribution 24
5.1.1 Great variations in mucinous and clear cell carcinoma 24
5.1.2 Different distributions patterns for clinical trial design 24
5.1.3 Taiwan pattern of OC- 24
5.1.4 Limitations 25
5.2 The frequency of genetic mutations in Taiwan HBOC 25
5.2.1 The prevalence of BRCA1/2 in HBOC in Taiwan 25
5.2.2 The frequency of genetic mutations in Taiwan HBOC 26
5.2.3 The distribution of cancer-predisposition genes in Taiwan 26
5.2.4 The correlation of clinical phenotypes and genotypes 27
5.3 POSTN in OC tumor microenvironment and chemo-resistance 28
5.3.1 New biomarker for OC chemo-response: Stromal stroma 28
5.3.2 POSTN expression in cancer stromal cells can be served as a
Poor prognostic marker for epithelial ovarian cancer. 28
5.3.3 POSTN expression in cancer stroma was correlated with advanced disease stage 29
5.3.4 POSTN treatment increased the resistance to cisplatin through AKT pathway 29
6.0 Conclusion 31
6.1 OC subtype distribution is heterogeneous 31
6.2 The frequency of genetic mutations in Taiwan HBOC is around 7-8% 31
6.3 POSTN in OC tumor microenvironment can server as a poor prognosis of clinical outcome and chemo-resistance 31
7.0 Perspective 32
7.1 The genomic subtype distribution of OC in worldwide. 32
7.2 The role of other extracellular matrix (ECM) molecular or immunologic pathway in OC platinum resistance 32
7.3 The homologous recombination deficiency in Taiwan and clinical application of PARP inhibitor in BRCA-deficiency patients 33
8.0 Reference 34
9.0 Tables 44
Table 1 .The detail of each studies include in this project. 44
Table 2. Frequency of germline pathogenic mutations in taiwanese hboc
patients. 47
Table 3. Partial list of partial lists of indels in BRCAchip 48
Table 4. Clinical characteristics of both groups 50
Table 5. Clinical characteristics of patients with pathogenic/likely pathogenic variants in the hospital cohort 51
Table 6. Clinical characteristics and bioinformatic analysis of variants of uncertain significance in the hospital cohort 52
Table 7. Detected pathogenic/likely pathogenic genes and their clinical surveillance 53
Table 8. Distribution of pathogenic/likely pathogenic mutations with respect
to family history, age at diagnosis and first cancer at diagnosis 55
Table 9. Distribution of pathogenic/likely pathogenic mutations with respect to
personal history 56
Table 10. The clinical pathological characteristics of patients with low and high
stromal periostin expression. 57
Table 11. Univariants and multivariate analysis of disease-specific
progression-free survival 58
Table 12. Univariants and multivariate analysis of disease-specific overall
survival 59
Table 13. The relationship between POSTN and platinum
Resistance 60
10. Figures 61
Figure 1. Flowchart illustrating the cross-sectional hospital cohort and
meta-analysis 61
Figure 2. BRCAchip Analysis System: ex. 2512delC 62
Figure 3. NGS gene coverage regions; ex. #51 CHEK2 64
Figure 4. Variants predictive summary in Bioinformatics website 65
Figure 5. Gene expression analysis of tumor for chemotherapy response in
OC 67
Figure 6. Tissue array construction and Immunohistochemistry (IHC) analysis
of 308 EOC patients. 68
Figure 7. Flow diagram of the steps in the reviewing process 69
Figure 8. Geographical distribution of relative frequency of serous subtype 70
Figure 9. Geographical distribution of relative frequency of mucinous subtype. 71
Figure 10. Geographical distribution of relative frequency of endometrioid subtype. 72
Figure 11. Geographical distribution of relative frequency of clear cell subtype 73
Figure 12. Dendrogram of hierarchical cluster analysis of distribution pattern
of subtypes among countries 74
Figure 13. A example of Pedigree (Family #42; BRCA1 2512delC)- 75
Figure 14. POSTN is upregulated in stroma of epithelial ovarian adenocarcinoma 76
Figure 15. Relative POSTN levels in GSE38666 77
Figure 16. Relative POSTN levels in GSE29156 78
Figure 17. Protein expression of POSTN can be observed in the cancer stroma
and cancer cells 79
Figure 18. Overexpression of stromal POSTN predicts worse survival compared to tumor POSTN in OC cancer patients 80
Figure19. Overall and diseases-free survival analysis stratified by combination
of stromal and tumor POSTN status. 81
Figure 20. POSTN induces platinum resistance 82
Figure 21. Two platinum response groups by using TCGA ovarian cancer 83
Figure 22. Western blot analysis in A2780 cells and A2780cp cells line 84
Figure 23. Western blot analysis in A2780 cells upon combinant POSTN
protein and/or MK-2206 treatment 85
Figure 24. Cytotoxicity assay of A2780 cells treated with cisplatin and AKT
inhibitor 86
Figure 25. Schematic model shows the relationship between stromal POSTN and platinum resistance in EOC 87
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