Clear Cell Carcinoma of the Endometrium Causing Paraneoplastic Retinopathy: Case Report and Review of the Literature

We reviewed the literature for cases in which gynecologic malignancies caused paraneoplastic retinopathy and ultimately led to blindness. Twenty-eight cases were derived from the literature, and one unique case is described from our institution. Of these 28 cases, 14 patients were diagnosed with endometrial cancer, 7 with ovarian cancer, 5 with cervical cancer, 1 fallopian tube cancer and 1 with concomitant endometrial and ovarian cancers. The average age of patients at the time of diagnosis was 64 years (range, 35–89 years). Typically, ocular manifestations antedate symptoms of the underlying carcinoma by 3–12 months. Information regarding the interval from visual symptoms to time of death is limited, but ranges from several months to several years. Our report is the first to document a clear cell carcinoma of the endometrium causing paraneoplastic retinopathy and is the first to review all gynecologic malignancies associated with visual paraneoplastic syndromes

Disturbed sleep is associated with reduced verbal episodic memory and entorhinal cortex volume in younger middle-aged women with risk-reducing early ovarian removal

INTRODUCTION: Women with early ovarian removal (&lt;48 years) have an elevated risk for both late-life Alzheimer's disease (AD) and insomnia, a modifiable risk factor. In early midlife, they also show reduced verbal episodic memory and hippocampal volume. Whether these reductions correlate with a sleep phenotype consistent with insomnia risk remains unexplored.METHODS: We recruited thirty-one younger middleaged women with risk-reducing early bilateral salpingo-oophorectomy (BSO), fifteen of whom were taking estradiol-based hormone replacement therapy (BSO+ERT) and sixteen who were not (BSO). Fourteen age-matched premenopausal (AMC) and seventeen spontaneously peri-postmenopausal (SM) women who were ~10y older and not taking ERT were also enrolled. Overnight polysomnography recordings were collected at participants' home across multiple nights (M=2.38 SEM=0.19), along with subjective sleep quality and hot flash ratings. In addition to group comparisons on sleep measures, associations with verbal episodic memory and medial temporal lobe volume were assessed.RESULTS: Increased sleep latency and decreased sleep efficiency were observed on polysomnography recordings of those not taking ERT, consistent with insomnia symptoms. This phenotype was also observed in the older women in SM, implicating ovarian hormone loss. Further, sleep latency was associated with more forgetting on the paragraph recall task, previously shown to be altered in women with early BSO. Both increased sleep latency and reduced sleep efficiency were associated with smaller anterolateral entorhinal cortex volume.DISCUSSION: Together, these findings confirm an association between ovarian hormone loss and insomnia symptoms, and importantly, identify an younger onset age in women with early ovarian removal, which may contribute to poorer cognitive and brain outcomes in these women.</p

Expression signatures of TP53 mutations in serous ovarian cancers

<p>Abstract</p> <p>Background</p> <p>Mutations in the <it>TP53 </it>gene are extremely common and occur very early in the progression of serous ovarian cancers. Gene expression patterns that relate to mutational status may provide insight into the etiology and biology of the disease.</p> <p>Methods</p> <p>The <it>TP53 </it>coding region was sequenced in 89 frozen serous ovarian cancers, 40 early stage (I/II) and 49 advanced stage (III/IV). Affymetrix U133A expression data was used to define gene expression patterns by mutation, type of mutation, and cancer stage.</p> <p>Results</p> <p>Missense or chain terminating (null) mutations in <it>TP53 </it>were found in 59/89 (66%) ovarian cancers. Early stage cancers had a significantly higher rate of null mutations than late stage disease (38% vs. 8%, p < 0.03). In advanced stage cases, mutations were more prevalent in short term survivors than long term survivors (81% vs. 30%, p = 0.0004). Gene expression patterns had a robust ability to predict <it>TP53 </it>status within training data. By using early versus late stage disease for out of sample predictions, the signature derived from early stage cancers could accurately (86%) predict mutation status of late stage cancers.</p> <p>Conclusions</p> <p>This represents the first attempt to define a genomic signature of <it>TP53 </it>mutation in ovarian cancer. Patterns of gene expression characteristic of <it>TP53 </it>mutation could be discerned and included several genes that are known p53 targets or have been described in the context of expression signatures of <it>TP53 </it>mutation in breast cancer.</p

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women.

An association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom-designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high-grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 1.2 × 10-6 , BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6-3.4, P = 1.6 × 10-5 , BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 2.3 × 10-5 , BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.Includes NIHR and CRUK

Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Funder: Funding details are provided in the Supplementary MaterialAbstractPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.</jats:p

Endometrial Cancer: Transitioning from Histology to Genomics

Endometrial carcinoma (EC) is traditionally treated with surgery and adjuvant treatment depending on clinicopathological risk factors. The genomic analysis of EC in 2013 and subsequent studies using immunohistochemistry have led to the current EC molecular classification into: polymerase epsilon mutated (POLEmut), p53 abnormal (p53abn), mismatch repair deficient (MMRd), and no specific molecular profile (NSMP). The four groups have prognostic value and represent a promising tool for clinical decision-making regarding adjuvant treatment. Molecular classification was integrated into the recent European Society of Gynecologic Oncology (ESGO) management guidelines. POLEmut EC has favorable outcomes and retrospective studies found that omitting adjuvant treatment is safe in this group; two prospective clinical trials, PORTEC-4 and TAPER, are ongoing to assess this. p53 abn is associated with increased recurrence, decreased survival, and benefitted from chemotherapy in the PORTEC-3 subgroup molecular analysis. The clinical trials PORTEC-4a and CANSTAMP will prospectively assess this. MMRd and NSMP groups have intermediate prognosis and will likely continue to rely closely on clinicopathological features for adjuvant treatment decisions. In addition, the molecular classification has led to exploring novel treatments such as checkpoint inhibitors. Overall, the molecular perspective on EC and associated clinical trials will likely refine EC risk stratification to optimize care and avoid overtreatment

High-throughput approaches for precision medicine in high-grade serous ovarian cancer

Abstract High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC