A study of patient-specific prognosis of ovarian cancer

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Survival prognosis in ovarian cancer

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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.

Cerebral correlates of cognitive reserve

Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved. Acknowledgements The Aberdeen birth Cohort Studies were established with grants to Lawrence Whalley by the Henry Smith Charity, the UK Biotechnology and Biological Sciences Research Council and a Professorial Clinical Fellowship Award from the Wellcome Trust. The imaging studies reported here were supported by grants to all three authors by the Chief Scientist Organisation of the Scottish Health Department and Alzheimer Research UK. We are grateful to the volunteers in the Aberdeen 1921 and 1936 Birth Cohort Studies and to our research colleagues in the Aberdeen biomedical Imaging Centre (Drs. Ahearn, Waiter, and Mustafa) and our long-term collaborators in the University of Edinburgh (Professors Deary and Starr at www.ccace.ed.ac.uk).

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.

Biodiversity survey of the UNESCO Sheka forest biosphere reserve from February 2016 to May 2016

Data of amphibians, reptiles and birds surveyed from February 2016 to May 2016 in the UNESCO Sheka forest biosphere reserve are provided as an online open access data file.

Water chemistry, carbonate system parameters, and macro-organism biomass of vent and off-vent sites in the Columbretes Islands Marine Reserve

Ocean acidification is receiving increasing attention because of its potential to affect marine ecosystems. Rare CO2 vents offer a unique opportunity to investigate the response of benthic ecosystems to acidification. However, the benthic habitats investigated so far are mainly found at very shallow water (less than or equal to 5 m depth) and therefore are not representative of the broad range of continental shelf habitats. Here, we show that a decrease from pH 8.1 to 7.9 observed in a CO2 vent system at 40 m depth leads to a dramatic shift in highly diverse and structurally complex habitats. Forests of the kelp Laminaria rodriguezii usually found at larger depths (greater than 65 m) replace the otherwise dominant habitats (i.e. coralligenous outcrops and rhodolith beds), which are mainly characterized by calcifying organisms. Only the aragonite-calcifying algae are able to survive in acidified waters, while high-magnesium-calcite organisms are almost completely absent. Although a long-term survey of the venting area would be necessary to fully understand the effects of the variability of pH and other carbonate parameters over the structure and functioning of the investigated mesophotic habitats, our results suggest that in addition of significant changes at species level, moderate ocean acidification may entail major shifts in the distribution and dominance of key benthic ecosystems at regional scale, which could have broad ecological and socio-economic implications.

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.

Synthetic Lethal Targeting of ARID1A-Mutant Ovarian Clear Cell Tumors with Dasatinib

New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G₁ -S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1Amutant OCCC. Mol Cancer Ther; 15(7); 1472-84. Ó2016 AACR.