Background: In vitro and observational epidemiological studies suggest that vitamin D may play a role in cancer prevention. However, the relationship between vitamin D and ovarian cancer is uncertain, with observational studies generating conflicting findings. A potential limitation of observational studies is inadequate control of confounding. To overcome this problem, we used Mendelian randomization (MR) to evaluate the association between single nucleotide polymorphisms (SNPs) associated with circulating 25-hydroxyvitamin D [25(OH)D] concentration and risk of ovarian cancer. Methods: We employed SNPs with well-established associations with 25(OH)D concentration as instrumental variables for MR: rs7944926 (DHCR7), rs12794714 (CYP2R1) and rs2282679 (GC). We included 31 719 women of European ancestry (10 065 cases, 21 654 controls) from the Ovarian Cancer Association Consortium, who were genotyped using customized Illumina Infinium iSelect (iCOGS) arrays. A two-sample (summary data) MR approach was used and analyses were performed separately for all ovarian cancer (10 065 cases) and for high-grade serous ovarian cancer (4121 cases). Results: The odds ratio for epithelial ovarian cancer risk (10 065 cases) estimated by combining the individual SNP associations using inverse variance weighting was 1.27 (95% confidence interval: 1.06 to 1.51) per 20 nmol/L decrease in 25(OH)D concentration. The estimated odds ratio for high-grade serous epithelial ovarian cancer (4121 cases) was 1.54 (1.19, 2.01). Conclusions: Genetically lowered 25-hydroxyvitamin D concentrations were associated with higher ovarian cancer susceptibility in Europeans. These findings suggest that increasing plasma vitamin D levels may reduce risk of ovarian cancer.

Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.

Background: The survival rate of patients with advanced high-grade serous ovarian carcinoma (HGSOC) remains disappointing. Clinically translatable orthotopic cell line xenograft models and patient-derived xenografts (PDXs) may aid the implementation of more personalised treatment approaches. Although orthotopic PDX reflecting heterogeneous molecular subtypes are considered the most relevant preclinical models, their use in therapeutic development is limited by lack of appropriate imaging modalities. Methods: We developed novel orthotopic xenograft and PDX models for HGSOC, and applied a near-infrared fluorescently labelled monoclonal antibody targeting the cell surface antigen CD24 for non-invasive molecular imaging of epithelial ovarian cancer. CD24-Alexa Fluor 680 fluorescence imaging was compared to bioluminescence imaging in three orthotopic cell line xenograft models of ovarian cancer (OV-90 luc+ , Skov-3 luc+ and Caov-3 luc+ , n = 3 per model). The application of fluorescence imaging to assess treatment efficacy was performed in carboplatin-paclitaxel treated orthotopic OV-90 xenografts (n = 10), before the probe was evaluated to detect disease progression in heterogenous PDX models (n = 7). Findings: Application of the near-infrared probe, CD24-AF680, enabled both spatio-temporal visualisation of tumour development, and longitudinal therapy monitoring of orthotopic xenografts. Notably, CD24-AF680 facilitated imaging of multiple PDX models representing different histological subtypes of the disease. Interpretation: The combined implementation of CD24-AF680 and orthotopic PDX models creates a state-ofthe-art preclinical platform which will impact the identification and validation of new targeted therapies, fluorescence image-guided surgery, and ultimately the outcome for HGSOC patients.

High-grade serous ovarian carcinoma (HGSOC) is characterised by alterations in the p53 pathway. The expression levels of p53 isoforms have been shown to be associated with patient survival in several cancers. This study examined the predictive and prognostic effects of the expression levels of TP53 pre-mRNA splicing isoforms and TP53 mutations in tumour tissues in 40 chemotherapy responders and 29 non-responders with HGSOC. The mRNA expression levels from total p53, and total Δ133p53, p53β, p53γ isoforms were determined by RT-qPCR, and TP53 mutation status by targeted massive parallel sequencing. The results from these analyses were correlated with the clinical outcome parameters. No differential expression of p53 isoforms could be detected between the chemosensitive and chemoresistant subgroups. In a multivariate Cox regression model, high levels of total Δ133p53 were found to be an independent prognosticator for improved overall survival (HR = 0.422, p = 0.018, 95% CI: 0.207–0.861) and reached borderline significance for progression-free survival (HR = 0.569, p = 0.061, 95% CI: 0.315–1.027). TP53 mutations resulting in loss of function or located at known hotspots were predictive of tumour characteristics and disease progression. These findings suggest that total Δ133p53 mRNA can be a biomarker for survival in HGSOC.