Objective: To report experience with borderline ovarian tumors (BOTs) in a developing country like Pakistan with limited resources and weak database of health system. Methods: Patients with BOTs managed at Shaukat Khanum Cancer hospital, Lahore, Pakistan from 2004 to 2014 were included and reviewed retrospectively. Data was recorded on histopathological types, age, CA-125, stage of disease, treatment modalities and outcomes. Results: Eighty-six patients with BOT were included with a median age of 35 years. Forty-two (49%) patients had serous BOTs and 43 (50%) had mucinous BOTs, while one (1%) had mixed type. Using FIGO staging, 80 patients had stage I; two patients had IIA, IIB and stage III each. Median follow-up time was 31.5 months. All patients had primary surgery. Seventy (81%) patients underwent complete surgical resection of tumor. Forty-three (50%) patients had fertility preserving surgery. Seventy-three (85%) patients remained in remission. Recurrent disease was observed in 13 (15%) patients. Median time to recurrence was 22 months. On further analysis, age above forty years, late stage at diagnosis and incomplete surgery were significantly associated with invasive recurrence. Conclusion: Despite a low malignant potential, relapses may occur in patients above forty years of age, incomplete surgery and staging information and advanced stage at presentation. Fertility sparing surgery should be considered in young patients. Complete excision of tumor and prolonged follow-up are advised because recurrence and transformation to invasive carcinoma may occur.

No description available.

Philosophiae Doctor - PhD / Introduction: Globally, there are over 190,000 new reported cases of ovarian cancers per annum. This comprises 3% to 4% of all cancers in women. Ovarian cancer is one of the leading causes of deaths in women. Ovarian cancer is the second most diagnosed gynaecological malignancy and over all the fifth cause leading to death among all types of cancer in the UK in 2004. More than 70% of epithelial ovarian cancers are diagnosed at an advanced stage. Consequently, the prognosis is poor and the mortality rate high. Thus, the survival rate is affected by how far the disease has progressed or spread. A dire need exists to identify ovarian cancer biomarkers, which could be used as good indicators of expression in ovarian cancer cells in vitro Aim: The aim of this study was to analyse selected cancer biomarkers, which are currently under intense investigation for their suitability to diagnose epithelial ovarian cancer at an early stage. These biomarkers were analysed in terms of their in vitro expression in normal epithelial cells and ovarian cancer cell lines, which allows for their genomic and proteomic classification. The expression analysis of each biomarker is related to the malignancy of a tumour and, therefore, advocates its use for potential future improvement of sensitive tumour markers. Methods: The primary human ovarian surface epithelial cell line (HOSEpiC), SKOV-3 cells and the OAW42 human epithelial ovarian tumour cell lines were used to evaluate the selected cancer biomarkers. Cells were cultured using appropriate media and supplements, and real-time quantitative polymerase chain reaction (RT-PCR) utilized to validate expression levels of the following genes: HDAC1, HDAC2, HDCA3, HDAC5, HDAC6, HDAC7, HDAC8, LPAR1, LPAR2, MUC16 and FOSL1, against normal housekeeping genes GAPDH and HPRT. In addition, immunocytochemistry was also used in the validation process of the aforementioned genes. Significance: ovarian cancer cells express gene signatures, which pose significant challenges for cancer drug development, therapeutics, prevention and management. The present study is an effort to explore ovarian cancer biomarkers to provide a better diagnostic method that may offer translational therapeutic possibilities to increase five- year survival rate. Results: HDAC5, HDAC6, LPAR1, LPAR2 and MUC16 expressed distinctively in ovarian cancers matched to other tissues or cancer types have already been identified by RT-QPCR and confirmed by immunocytochemistry and efforts to generate monoclonal antibodies to the other six genes (HDAC1, HDAC2, HDAC3, HDAC7, HDAC8 and FOSL1) encoded proteins are underway. Conclusions: here we provide strong evidence suggesting that HDAC5, HDAC6, LPAR1, LPAR2, except MUC16 are up regulated in ovarian cancer. These data were confirmed by examining Human Protein Atlas (HPA) databases, in addition to protein expression of HDAC5, HDAC6, LPAR1, LPAR2 and MUC16 in cells cytoplasm. For future prospective, using other techniques that assess the variant expression that could explain the release of these gene candidates into the circulation with serum tumour markers, and protein expression will be strengthened.

Background: Due to the “flare effect” associated with the flare protocol, variation in the degree of follicular maturation during stimulation may result in differences in follicle response as compared to the luteal protocol which is based on maximal pituitary suppression and synchronization of follicular maturation. In this study, besides other methods, Anti-Mullerian Hormone (AMH), a novel marker for ovarian reserve, was used as a tool to evaluate the ovarian responsiveness to stimulation. Methods: Women undergoing IVF/ICSI treatment in the UBC IVF Program from January to December 2006 using luteal and flare protocols were retrospectively selected for a total of 40 treatment cycles, 20 cycles in each protocol matched by age, weight, and indication for IVF/ICSI. Serial serum Estradiol (E₂) levels and follicle data were obtained from the clinic chart. Follicle stimulating hormone (FSH), Luteinizing Hormone (LH), progesterone (P), androstenedione (D₄) and AMH levels were measured from aliquots of frozen serum samples. Hormone responses were evaluated by Area Under the Curve (AUC). Data were analyzed using the t-test and statistical significance was considered present at P<0.05. Results are reported as the mean ± SEM. Results: For flare versus luteal protocol, there was a significant difference in the number of total follicles (14.5 ± 1.8 vs 21.3 ± 2.3), medium follicles (3.7 ± 0.6 vs 8.4 ± 1.3), eggs retrieved (8 ± 0.8 vs 14 ± 1.4) and oocytes fertilized (4.4 ± 0.5 vs 8.4 ± 0.7), AMH AUC (62 ± 12 vs 111 ± 13), LH AUC (67 ± 21 vs 20 ± 9), FSH AUC (171 ± 59 vs 112 ± 29), respectively. Mean number of embryos transferred in both groups was similar. Number of pregnancies conceived (5 for flare and 10 for luteal protocol) was not significantly different. Although E₂ AUC in luteal protocol was higher than that in flare protocol, the difference was not statistically significant (28,339 ± 2,669 vs 26,905 ± 2,790). Differences in P and D₄ AUC between the two protocols were not statistically significant. Correlations with ovarian follicles and eggs retrieved were better for AMH than E₂. Conclusions: The luteal protocol exhibited a better ovarian response to stimulation as compared to the flare protocol. As compared to E₂, AMH had a better correlation with the number of follicles and eggs retrieved.

Epidemiological studies have described a link between chronic inflammatory conditions, such as diabetes or obesity, and EOC suggesting that systemic inflammation may increase the risk of the disease. The purpose of this study was to identify the impact of prolonged exposure to low-grade inflammation on EOC tumorigenicity. We hypothesized that exposure to this inflammation would accelerate ovarian tumor growth. In vitro, normal and transformed ovarian epithelial cells had limited responsiveness to inflammatory cytokines. In vivo, LPS-induced low-grade chronic systemic inflammation accelerated EOC progression primarily through enhanced angiogenesis. Evaluation of the relationships between chronic systemic inflammation and EOC may provide a role for anti-inflammatory treatment in combinational EOC therapies. Additionally, as the rate of metabolic disorders increases in the Western world the results from this work may facilitate the advancement of complimentary therapeutic interventions for other cancers that are influenced by inflammation.

Background: Due to the “flare effect” associated with the flare protocol, variation in the degree of follicular maturation during stimulation may result in differences in follicle response as compared to the luteal protocol which is based on maximal pituitary suppression and synchronization of follicular maturation. In this study, besides other methods, Anti-Mullerian Hormone (AMH), a novel marker for ovarian reserve, was used as a tool to evaluate the ovarian responsiveness to stimulation. Methods: Women undergoing IVF/ICSI treatment in the UBC IVF Program from January to December 2006 using luteal and flare protocols were retrospectively selected for a total of 40 treatment cycles, 20 cycles in each protocol matched by age, weight, and indication for IVF/ICSI. Serial serum Estradiol (E₂) levels and follicle data were obtained from the clinic chart. Follicle stimulating hormone (FSH), Luteinizing Hormone (LH), progesterone (P), androstenedione (D₄) and AMH levels were measured from aliquots of frozen serum samples. Hormone responses were evaluated by Area Under the Curve (AUC). Data were analyzed using the t-test and statistical significance was considered present at P<0.05. Results are reported as the mean ± SEM. Results: For flare versus luteal protocol, there was a significant difference in the number of total follicles (14.5 ± 1.8 vs 21.3 ± 2.3), medium follicles (3.7 ± 0.6 vs 8.4 ± 1.3), eggs retrieved (8 ± 0.8 vs 14 ± 1.4) and oocytes fertilized (4.4 ± 0.5 vs 8.4 ± 0.7), AMH AUC (62 ± 12 vs 111 ± 13), LH AUC (67 ± 21 vs 20 ± 9), FSH AUC (171 ± 59 vs 112 ± 29), respectively. Mean number of embryos transferred in both groups was similar. Number of pregnancies conceived (5 for flare and 10 for luteal protocol) was not significantly different. Although E₂ AUC in luteal protocol was higher than that in flare protocol, the difference was not statistically significant (28,339 ± 2,669 vs 26,905 ± 2,790). Differences in P and D₄ AUC between the two protocols were not statistically significant. Correlations with ovarian follicles and eggs retrieved were better for AMH than E₂. Conclusions: The luteal protocol exhibited a better ovarian response to stimulation as compared to the flare protocol. As compared to E₂, AMH had a better correlation with the number of follicles and eggs retrieved.

Thesis (M.S.)--University of Wisconsin--Madison, 1982. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 83-86).

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 41-49).

Background: Due to the “flare effect” associated with the flare protocol, variation in the degree of follicular maturation during stimulation may result in differences in follicle response as compared to the luteal protocol which is based on maximal pituitary suppression and synchronization of follicular maturation. In this study, besides other methods, Anti-Mullerian Hormone (AMH), a novel marker for ovarian reserve, was used as a tool to evaluate the ovarian responsiveness to stimulation. Methods: Women undergoing IVF/ICSI treatment in the UBC IVF Program from January to December 2006 using luteal and flare protocols were retrospectively selected for a total of 40 treatment cycles, 20 cycles in each protocol matched by age, weight, and indication for IVF/ICSI. Serial serum Estradiol (E₂) levels and follicle data were obtained from the clinic chart. Follicle stimulating hormone (FSH), Luteinizing Hormone (LH), progesterone (P), androstenedione (D₄) and AMH levels were measured from aliquots of frozen serum samples. Hormone responses were evaluated by Area Under the Curve (AUC). Data were analyzed using the t-test and statistical significance was considered present at P<0.05. Results are reported as the mean ± SEM. Results: For flare versus luteal protocol, there was a significant difference in the number of total follicles (14.5 ± 1.8 vs 21.3 ± 2.3), medium follicles (3.7 ± 0.6 vs 8.4 ± 1.3), eggs retrieved (8 ± 0.8 vs 14 ± 1.4) and oocytes fertilized (4.4 ± 0.5 vs 8.4 ± 0.7), AMH AUC (62 ± 12 vs 111 ± 13), LH AUC (67 ± 21 vs 20 ± 9), FSH AUC (171 ± 59 vs 112 ± 29), respectively. Mean number of embryos transferred in both groups was similar. Number of pregnancies conceived (5 for flare and 10 for luteal protocol) was not significantly different. Although E₂ AUC in luteal protocol was higher than that in flare protocol, the difference was not statistically significant (28,339 ± 2,669 vs 26,905 ± 2,790). Differences in P and D₄ AUC between the two protocols were not statistically significant. Correlations with ovarian follicles and eggs retrieved were better for AMH than E₂. Conclusions: The luteal protocol exhibited a better ovarian response to stimulation as compared to the flare protocol. As compared to E₂, AMH had a better correlation with the number of follicles and eggs retrieved. / Medicine, Faculty of / Obstetrics and Gynaecology, Department of / Graduate

Ovarian cancer is the most fatal of all gynecological malignancies. Epithelial ovarian cancer (EOC) accounts for about 90% of malignant ovarian tumours and is thought to originate mostly from ovarian surface epithelium (OSE) cells. Epidemiological data suggest that hormone replacement treatment (HRT) users have a higher risk of ovarian cancer, which is related to the use of oestrogen-only HRT. In addition, EOC is oestrogen responsive. This thesis reveals the capacity for production and metabolism of oestrogen in normal OSE and malignant primary EOC cells, and describes the action of oestrogen in the development of EOC at three levels. First, the expression of the genes encoding oestrogen production and metabolism and oestrogen receptor (ER) was investigated in OSE and EOC cells at RNA and protein levels. Immunohistochemistry revealed that steroid sulphatase (STS), oestrogen sulfotransferase (EST), 17βhydroxysteroid dehydrogenase (17βHSD) 2 and 17βHSD5 proteins were present in pre-menopausal, post-menopausal and inclusion cystic OSE as well as EOC cells. Taqman qRT-PCR revealed STS, EST, 17βHSD1, 17βHSD2, 17βHSD5, ERα, ERβ and oestrone sulphate (E1S) transporters such as organic anion transporting polypeptide (OATP)-B, OATP-D and OATP-E mRNAs were expressed in pre-menopausal OSE and EOC at different levels. When basal mRNA levels were compared among untreated samples of pre-menopausal OSE and EOC, EST mRNA expression was significantly higher in the OSE compared to EOC cells (P<0.05) while OATP-B mRNA level was the opposite (P<0.05). Radiometric enzyme activity assays demonstrated different metabolism patterns of E1S and oestrone (E1) between normal and malignant cells, indicating overall activities of STS and 17βHSD1 or 17βHSD5 to be higher than the overall activities of EST and 17βHSD2 in cancer cells while enzyme activities in OSE cells were opposite to this. Second, the impact of inflammation on oestrogen production, metabolism and action was compared in OSE and EOC cells by testing the response of target genes to a panel of pro-inflammatory cytokines. The data revealed that in OSE cells, EST (P<0.01) and 17βHSD2 (P<0.001) mRNAs were decreased while ERα mRNA (P<0.001) was increased by IL-1α. In addition, EST mRNA was inhibited by IL-4 (P<0.05). In SKOV-3 (EOC cell line) cells, IL-1α stimulated STS mRNA (P<0.001)and enzyme activity (P<0.05). Moreover, IL-4 inhibited (P<0.05) while IL-8 and IL- 10 enhanced (P<0.01) ERα mRNA levels. Finally, the effect of oestrogenic components of HRT medication (equilin and equilin-sulphate) on the expression of cancer-associated genes was compared to that of 17β-oestradiol (E2) in PEO-1 (an oestrogen-responsive EOC cell line) cells. Expression of the oestrogen-responsive genes FN1 and IGFBP3 mRNA expression was similarly inhibited by E2 and equilin (P<0.05) as well as E1S and sodium equilin-sulphate (P<0.05). In conclusion, this thesis presents evidence that intracrine oestrogen formation and metabolism differs between OSE and EOC cells, such that E2 formation is inhibited in normal OSE but is promoted in EOC. Inflammatory cytokines also influence the local production of E2 by regulating genes encoding oestrogen production and metabolism and receptors. Finally, local HRT metabolites can regulate cancer-associated gene expression in EOC. Together, these data suggest a role for local oestrogen production and action in inflammation-associated development of EOC. Conversely, differential regulation of the same parameters in OSE cells from premenopausal women minimizes oestrogen formation and ‘protects’ against the promotion of EOC.