Search

BackgroundObservational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias.MethodsWe pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis.ResultsGreater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours.ConclusionsWomen with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.

Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS [56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low-malignant potential (LMP) serous, and 24 for invasive serous EOC], selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95 % confidence intervals are reported. Nine variants tagging six loci were associated with subtype-specific EOC risk at P

The study aims to investigate four adult-type granulosa-cell tumors (GCTs) of the ovary and the role of FOXL2 mutation in the pathogenesis of GCTs. The results indicate that mutant FOXL2 is responsible for adult-type GCTs of the ovary.

Abstract Background The response rate of ovarian mucinous carcinomas to paclitaxel/carboplatin is low, prompting interest in targeted molecular therapies. We investigated HER2 expression and amplification, and the potential for trastuzumab therapy in this histologic subtype of ovarian cancer. Methods HER2 status was tested in 33 mucinous carcinomas and 16 mucinous borderline ovarian tumors (BOT)). Five cases with documented recurrence and with tissue from the recurrence available for testing were analyzed to determine whether HER2 amplification status changed over time. Three prospectively identified recurrent mucinous ovarian carcinomas were assessed for HER2 amplification and patients received trastuzumab therapy with conventional chemotherapy. Results Amplification of HER2 was observed in 6/33 (18.2%) mucinous carcinomas and 3/16 (18.8%) BOT. HER2 amplification in primary mucinous carcinomas was not associated with an increased likelihood of recurrence. The prospectively identified recurrent mucinous carcinomas showed overexpression and amplification of HER2; one patient's tumor responded dramatically to trastuzumab in combination with conventional chemotherapy, while another patient experienced an isolated central nervous system recurrence after trastuzumab therapy. Conclusion HER2 amplification is relatively common in ovarian mucinous carcinomas (6/33, 18.2%), although not of prognostic significance. Trastuzumab therapy is a treatment option for patients with mucinous carcinoma when the tumor has HER2 amplification and overexpression.

Ovarian cancer exhibits a wide spectrum of behavior, the effectiveness of therapies varies and the circumstances of patients differ. Better outcomes will require more selective treatment strategies considerate of these variables. The need for treatment As long as outcome is affected more by disease than by treatment, survival will be determined by the bulk and growth-rate of residual tumor - prognostic factors reflect these. They indicate the need for treatment, but not whether benefit is likely. FIGO stage is the international standard, but this alone is inadequately predictive. Grade reflects virulence, but subjectivity has limited its usefulness. Newer quantitative pathology techniques (such as DNA ploidy) more reproducibly reflect behavior. Prognostic factors can be used to define subsets of patients at differing degrees of disease risk., Efficacy of treatment No response predictors are yet of practical use in selecting primary chemotherapy on an individual basis. Generally, response is more likely if the tumor is less extensive and if dose and treatment frequency are higher. Monitoring biomarkers can more quickly identify those with a suboptimal response who may require a change or discontinuation of treatment. Re-laparotomy has limited usefulness. Response predictors for second-line treatment (e.g. the failure-free interval) are available and also have implications for new drug testing., Suitability of treatment Advanced age or serious additional illness may render intensive treatment inappropriate. The informed patient's wishes are of prime importance., An evolving strategy of selective management is described. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS (56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low malignant potential (LMP) serous, and 24 for invasive serous EOC), selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95% confidence intervals are reported. Nine variants tagging 6 loci were associated with subtype-specific EOC risk at P<0.05, and had an OR that agreed in direction of effect with the GWAS results. Several of these variants are in or near genes with a biological rationale for conferring EOC risk, including ZFP36L1 and RAD51B for mucinous EOC (rs17106154, OR=1.17, P=0.029, n=1,483 cases), GRB10 for endometrioid and clear cell EOC (rs2190503, P=0.014, n=2,903 cases), and C22orf26/BPIL2 for LMP serous EOC (rs9609538, OR=0.86, P=0.0043, n=892 cases). In analyses that included the 75 GWAS samples, the association between rs9609538 (OR=0.84, P=0.0007) and LMP serous EOC risk remained statistically significant at P<0.0012 adjusted for multiple testing. Replication in additional samples will be important to verify these results for the less-common EOC subtypes.

Abstract: Objective: An ability to predict survival is of crucial importance in determining the need for cancer therapy. Recent advances in tumor typing of ovarian carcinomas lead to a classification which is more reproducible and reflects underlying biology more accurately than grade. We tested whether updated tumor type predicts outcome for patients with low-stage ovarian carcinoma. Methods: From a population-based cohort of 1326 women diagnosed with stage I–II ovarian carcinoma between 1984 and 2003, 652 cases were available for central pathological slide review using contemporary criteria. Six hundred thirty cases were confirmed as ovarian carcinoma. Twenty-five ovarian carcinomas of rare types were excluded leaving 605 cases for this study. Recursive partitioning analysis and univariate models were used to identify subsets with an excellent outcome, i.e., disease-specific survival at 10 years (DSS10y) ≥95%. Results: Seventy-seven ovarian carcinomas of endometrioid and mucinous type, stage Ia or Ib, were associated with an excellent outcome [DSS10y=95%]. No subset of the high-grade serous type with an excellent outcome could be identified. Clear cell carcinomas of stage Ia or Ib had a favorable outcome [DSS10y=87%] compared to stage Ic–II [DSS10y=66%]. Conclusions: A subset of ovarian carcinoma patients with an excellent outcome can be identified based on tumor type (endometrioid or mucinous) and stage (Ia or Ib). Type is more reproducibly assigned than grade and identifies a larger cohort of women with stage I/II ovarian carcinoma with favorable outcomes (12.2% vs. 6.5%), and therefore is superior to grade in estimating risk of death from ovarian carcinoma. [Copyright &y& Elsevier]

Abstract: Objectives: Uterine MMMTs are aggressive malignancies that are rarely cured by purely local therapies. Effective chemotherapy is needed. The phase III proven, ifosfamide-based combinations are inconvenient and costly. Carboplatin and paclitaxel (CT) are easy to deliver and is effective against endometrial carcinoma and should be against MMMT (as they are now regarded as epithelial in nature). Methods: A review of all women with uterine MMMT treated with CT. Paclitaxel 175 mg/m2 over 3 h preceded carboplatin (AUC 5–6) every 4 weeks for 3–6 cycles±subsequent pelvic irradiation. Results: Twenty-eight newly diagnosed women (20 evaluable) and 12 recurrent (11 evaluable) were treated. Response rates were 60% (12 of 20, CR 5, PR 7) and 55% (6 of 11, CR 2, PR 4) with median PFS of 16 and 12 months. Dose reduction occurred in 5%, treatment delay in 10%. Conclusions: Carboplatin–paclitaxel is effective against uterine MMMT, with similar efficacy to ifosfamide combinations. It is more convenient, less costly and easy to deliver. [Copyright &y& Elsevier]

Background: Observational studies have reported a positive association between body mass index (BMI) and ovarian cancer risk. However, questions remain as to whether this represents a causal effect, or holds for all histological subtypes. The lack of association observed for serous cancers may, for instance, be due to disease-associated weight loss. Mendelian randomization (MR) uses genetic markers as proxies for risk factors to overcome limitations of observational studies. We used MR to elucidate the relationship between BMI and ovarian cancer, hypothesizing that genetically predicted BMI would be associated with increased risk of non-high grade serous ovarian cancers (non-HGSC) but not HGSC., Methods: We pooled data from 39 studies (14 047 cases, 23 003 controls) in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS, partial F-statistic = 172), summing alleles at 87 single nucleotide polymorphisms previously associated with BMI, weighting by their published strength of association with BMI. Applying two-stage predictor-substitution MR, we used logistic regression to estimate study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted BMI and risk, and pooled these using random-effects meta-analysis., Results: Higher genetically predicted BMI was associated with increased risk of non-HGSC (pooled OR = 1.29, 95% CI 1.03-1.61 per 5 units BMI) but not HGSC (pooled OR = 1.06, 95% CI 0.88-1.27). Secondary analyses stratified by behaviour/subtype suggested that, consistent with observational data, the association was strongest for low-grade/borderline serous cancers (OR = 1.93, 95% CI 1.33-2.81)., Conclusions: Our data suggest that higher BMI increases risk of non-HGSC, but not the more common and aggressive HGSC subtype, confirming the observational evidence., (© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)