A study of patient-specific prognosis of ovarian cancer

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Survival prognosis in ovarian cancer

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The endocrine basis for reproductive life-history trade-offs during the previtellogenic resting stage in the yellow fever mosquito, Aedes Aegypti

Juvenile hormone (JH) is the central hormonal regulator of life-history trade-offs in many insects. In Aedes aegypti, JH regulates reproductive development after emergence. Little is known about JH's physiological functions after reproductive development is complete or JH's role in mediating life-history trade-offs. By examining the effect of hormones, nutrition, and mating on ovarian physiology during the previtellogenic resting stage, critical roles were determined for these factors in mediating life-history trade-offs and reproductive output. The extent of follicular resorption during the previtellogenic resting stage is dependent on nutritional quality. Feeding females a low quality diet during the resting stage causes the rate of follicular resorption to increase and reproductive output to decrease. Conversely, feeding females a high quality diet causes resorption to remain low. The extent of resorption can be increased by separating the ovaries from a source of JH or decreased by exogenous application of methoprene. Active caspases were localized to resorbing follicles indicating that an apoptosis-like mechanism participates in follicular resorption. Accumulations of neutral lipids and the accumulation of mRNA's integral to endocytosis and oocyte development such as the vitellogenin receptor (AaVgR), lipophorin receptor (AaLpRov), heavy-chain clathrin (AaCHC), and ribosomal protein L32 (rpL32) were also examined under various nutritional and hormonal conditions. The abundance of mRNA's and neutral lipid content increased within the previtellogenic ovary as mosquitoes were offered increasing sucrose concentrations or were treated with methoprene. These same nutritional and hormonal manipulations altered the extent of resorption after a blood meal indicating that the fate of follicles and overall fecundity depends, in part, on nutritional and hormonal status during the previtellogenic resting stage. Mating female mosquitoes also altered follicle quality and resorption similarly to nutrition or hormonal application and demonstrates that male accessory gland substances such as JH III passed to the female during copulation have a strong effect on ovarian physiology during the previtellogenic resting stage and can influence reproductive output. Taken together these results demonstrate that the previtellogenic resting stage is not an inactive period but is instead a period marked by extensive life-history and fitness trade-offs in response to nutrition, hormones and mating stimuli.

Novel NR5A1 Missense Mutation in Premature Ovarian Failure: Detection in Han Chinese Indicates Causation in Different Ethnic Groups

Background The etiology of most premature ovarian failure (POF) cases is usually elusive. Although genetic causes clearly exist and a likely susceptible region of 8q22.3 has been discovered, no predominant explanation exists for POF. More recently, evidences have indicated that mutations in NR5A1 gene could be causative for POF. We therefore screened for mutations in the NR5A1 gene in a large cohort of Chinese women with non-syndromic POF. Methods Mutation screening of NR5A1 gene was performed in 400 Han Chinese women with well-defined 46,XX idiopathic non-syndromic POF and 400 controls. Subsequently, functional characterization of the novel mutation identified was evaluated in vitro. Results A novel heterozygous missense mutation [c.13T>G (p.Tyr5Asp)] in NR5A1 was identified in 1 of 384 patients (0.26%). This mutation impaired transcriptional activation on Amh, Inhibin-a, Cyp11a1and Cyp19a1 gene, as shown by transactivation assays. However, no dominant negative effect was observed, nor was there impact on protein expression and nuclear localization. Conclusions This novel mutation p.Tyr5Asp, in a novel non-domain region, is presumed to result in haploinsufficiency. Irrespectively, perturbation in NR5A1 is not a common explanation for POF in Chinese.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

ROLE OF STAT1 AND CXCL10 IN THE TUMOUR IMMUNE MICROENVIRONMENT OF HIGH-GRADE SEROUS OVARIAN CANCER

High-grade serous ovarian cancer (HGSC) is the most prevalent epithelial ovarian cancer characterized by late detection, metastasis and resistance to chemotherapy. Previous studies on the tumour immune microenvironment in HGSC identified STAT1 and CXCL10 as the most differentially expressed genes between treatment naïve chemotherapy resistant and sensitive tumours. Interferon-induced STAT1 is a transcription factor, which induces many genes including tumour suppressor genes and those involved in recruitment of immune cells to the tumour immune microenvironment (TME), including CXCL10. CXCL10 is a chemokine that recruits tumour infiltrating lymphocytes (TILs) and exhibits angiostatic function. The current study was performed to determine the effects of differential STAT1 and CXCL10 expression on HGSC disease progression and TME. STAT1 expression and intratumoural CD8+ T cells were evaluated as prognostic and predictive biomarkers via immunohistochemistry on 734 HGSC tumours accrued from the Terry Fox Research Institute-Canadian Ovarian Experimental Unified Resource. The combined effect of STAT1 expression and CD8+ TIL density was confirmed as prognostic and predictive companion biomarkers in the second independent biomarker validation study. Significant positive correlation between STAT1 expression and intratumoral CD8+ TIL density was observed. The effects of enforced CXCL10 expression on HGSC tumour growth, vasculature and immune tumour microenvironment were studied in the ID8 mouse ovarian cancer cell engraftment in immunocompetent C57BL/6 mice. Significant decrease in tumour progression in mice injected with ID8 CXCL10 overexpressing cells compared to mice injected with ID8 vector control cells was observed. Multiplexed cytokine analysis of ascites showed differential expression of IL-6, VEGF and CXCL9 between the two groups. Endothelial cell marker staining showed differences in tumour vasculature between the two groups. Immune transcriptomic profiling identified distinct expression profiles in genes associated with cytokines, chemokines, interferons, T cell function and apoptosis between the two groups. These findings provide evidence that STAT1 is an independent biomarker and in combination with CD8+ TIL density could be applied as novel immune-based biomarkers in HGSC. These results provide the basis for future studies aimed at understanding mechanisms underlying differential tumour STAT1 and CXCL10 expression and its role in pre-existing tumour immunologic diversity, thus potentially contributing to biomarker guided immune modulatory therapies.

Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Identification of potentially pathogenic variants in candidate breast and ovarian cancer susceptibility genes in BRCAX patients

Mutations within the BRCA1 and BRCA2 genes account for approximately 20% of hereditary breast cancers, with a further 10%–15% being attributable to rare mutations in moderate-risk genes and common variants in low-risk genes. The genes harbouring mutations in the remaining ∼65% of hereditary breast cancers are unknown. The identification of mutation carriers in hereditary breast and ovarian cancer (hboc) families is critical for determining who is most at risk of developing the disease and therefore who should be offered risk-reducing procedures or more intensive screening, or both.

Many of the high- and moderate-risk genes for hereditary breast cancers encode proteins that work in concert to maintain genomic stability and in dna damage signalling and repair. A novel BRCA1 protein complex identified within the research group whose target genes are involved in dna repair provided novel candidates for hboc susceptibility genes. These 12 candidate genes were sequenced in a cohort of 675 affected individuals from the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) with hereditary breast or ovarian cancer, but with no mutations in known susceptibility genes (BRCAx patients). This analysis identified 20 individuals (each from a different BRCAx family) with different potentially pathogenic variants across 6 of the candidate hboc susceptibility genes. The family members of each BRCAx index case were tested for the presence of the specific mutation identified in the proband to examine segregation with disease. To further expand on the potential role of the novel candidate hboc susceptibility genes identified in this study, the genetic variation of a second cohort of 520 Northern Irish BRCAx patients is being characterized using a 61-gene panel.