High throughput detection of M6P/IGF2R intronic hypermethylation and LOH in ovarian cancer

Cell surface mannose 6-phosphate/insulin-like growth factor II receptors (M6P/IGF2R) bind and target exogenous insulin-like growth factor II (IGF2) to the prelysosomes where it is degraded. Loss of heterozygosity (LOH) for M6P/IGF2R is found in cancers, with mutational inactivation of the remaining allele. We exploited the normal allele-specific differential methylation of the M6P/IGF2R intron 2 CpG island to rapidly evaluate potential LOH in ovarian cancers, since every normal individual is informative. To this end, we developed a method for bisulfite modification of genomic DNA in 96-well format that allows for rapid methylation profiling. We identified ovarian cancers with M6P/IGF2R LOH, but unexpectedly also found frequent abnormal acquisition of methylation on the paternally inherited allele at intron 2. These results demonstrate the utility of our high-throughput method of bisulfite modification for analysis of large sample numbers. They further show that the methylation status of the intron 2 CpG island may be a useful indicator of LOH and biomarker of disease

Robotic-Assisted Laparoscopic Gynecologic Procedures in a Fellowship Training Program

An early evaluation of the feasibility of training fellows in robotic surgery suggests that it is feasible to incorporate a systematic approach to robotic-assisted laparoscopic training at the onset of incorporating this technology into current practice

Mechanical Stiffness Grades Metastatic Potential in Patient Tumor Cells and in Cancer Cell Lines

Cancer cells are defined by their ability to invade through the basement membrane, a critical step during metastasis. While increased secretion of proteases, which facilitates degradation of the basement membrane, and alterations in the cytoskeletal architecture of cancer cells have been previously studied, the contribution of the mechanical properties of cells in invasion is unclear. Here we apply a magnetic tweezer system to establish that stiffness of patient tumor cells and cancer cell lines inversely correlates with migration and invasion through three-dimensional basement membranes, a correlation known as a power law. We found that cancer cells with the highest migratory and invasive potential are five times less stiff than cells with the lowest migration and invasion potential. Moreover, decreasing cell stiffness by pharmacological inhibition of myosin II increases invasiveness, while increasing cell stiffness by restoring expression of the metastasis suppressor TβRIII/betaglycan decreases invasiveness. These findings are the first demonstration of the power law relation between the stiffness and the invasiveness of cancer cells and show that mechanical phenotypes can be used to grade the metastatic potential of cell populations with the potential for single cell grading. The measurement of a mechanical phenotype, taking minutes rather than hours needed for invasion assays, is promising as a quantitative diagnostic method and as a discovery tool for therapeutics. By demonstrating that altering stiffness predictably alters invasiveness, our results indicate that pathways regulating these mechanical phenotypes are novel targets for molecular therapy of cancer

A Targeted Genetic Association Study of Epithelial Ovarian Cancer Susceptibility

BACKGROUND: Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci. RESULTS: At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p \u3c5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p\u3c 3x10-6). METHODS: A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure. CONCLUSION: Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance

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

Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): Methodology for a Population-Based Study of Black, Hispanic and White Patients with Ovarian Cancer

INTRODUCTION: Less than 40% of patients with ovarian cancer (OC) in the USA receive stage-appropriate guideline-adherent surgery and chemotherapy. Black patients with cancer report greater depression, pain and fatigue than white patients. Lack of access to healthcare likely contributes to low treatment rates and racial differences in outcomes. The Ovarian Cancer Epidemiology, Healthcare Access and Disparities study aims to characterise healthcare access (HCA) across five specific dimensions-Availability, Affordability, Accessibility, Accommodation and Acceptability-among black, Hispanic and white patients with OC, evaluate the impact of HCA on quality of treatment, supportive care and survival, and explore biological mechanisms that may contribute to OC disparities. METHODS AND ANALYSIS: We will use the Surveillance Epidemiology and Ends Results dataset linked with Medicare claims data from 9744 patients with OC ages 65 years and older. We will recruit 1641 patients with OC (413 black, 299 Hispanic and 929 white) from cancer registries in nine US states. We will examine HCA dimensions in relation to three main outcomes: (1) receipt of quality, guideline adherent initial treatment and supportive care, (2) quality of life based on patient-reported outcomes and (3) survival. We will obtain saliva and vaginal microbiome samples to examine prognostic biomarkers. We will use hierarchical regression models to estimate the impact of HCA dimensions across patient, neighbourhood, provider and hospital levels, with random effects to account for clustering. Multilevel structural equation models will estimate the total, direct and indirect effects of race on treatment mediated through HCA dimensions. ETHICS AND DISSEMINATION: Result dissemination will occur through presentations at national meetings and in collaboration with collaborators, community partners and colleagues across othercancer centres. We will disclose findings to key stakeholders, including scientists, providers and community members. This study has been approved by the Duke Institutional Review Board (Pro00101872). Safety considerations include protection of patient privacy. All disseminated data will be deidentified and summarised

Hormonal Risk Factors for Ovarian Cancer in Premenopausal and Postmenopausal Women

Ovarian cancer is most frequently diagnosed in postmenopausal women; however, the strongest risk predictors, pregnancy and oral contraceptive use, occur in most women in their twenties and thirties. Relatively few studies have examined how reproductive risk factors vary between pre- and postmenopausal ovarian cancer. The authors used data from a population-based, case-control study of ovarian cancer (896 cases, 967 controls) conducted in North Carolina from 1999 to 2006. Odds ratios and 95% confidence intervals were calculated by using unconditional logistic regression. Inverse associations with ovarian cancer were observed with duration of oral contraceptive use, later age at last use, and more recent use among premenopausal women; no significant associations were found for postmenopausal women. Analyses limited to oral contraceptive users showed that duration was a more significant predictor of risk than was timing of use. Parity was inversely associated with premenopausal but not postmenopausal ovarian cancer. Later age at pregnancy was associated with reduced risk for both pre- and postmenopausal women. Analyses among parous women showed that pregnancy timing was a stronger risk predictor than number of pregnancies. Findings suggest that associations between ovarian cancer and reproductive characteristics vary by menopausal status. Additional research is needed to further elucidate risk factors for postmenopausal disease

Evaluating the role of alcohol consumption in breast and ovarian cancer susceptibility using population-based cohort studies and two-sample Mendelian randomization analyses.

Alcohol consumption is correlated positively with risk for breast cancer in observational studies, but observational studies are subject to reverse causation and confounding. The association with epithelial ovarian cancer (EOC) is unclear. We performed both observational Cox regression and two-sample Mendelian randomization (MR) analyses using data from various European cohort studies (observational) and publicly available cancer consortia (MR). These estimates were compared to World Cancer Research Fund (WCRF) findings. In our observational analyses, the multivariable-adjusted hazard ratios (HR) for a one standard drink/day increase was 1.06 (95% confidence interval [CI]; 1.04, 1.08) for breast cancer and 1.00 (0.92, 1.08) for EOC, both of which were consistent with previous WCRF findings. MR ORs per genetically predicted one standard drink/day increase estimated via 34 SNPs using MR-PRESSO were 1.00 (0.93, 1.08) for breast cancer and 0.95 (0.85, 1.06) for EOC. Stratification by EOC subtype or estrogen receptor status in breast cancers made no meaningful difference to the results. For breast cancer, the CIs for the genetically derived estimates include the point-estimate from observational studies so are not inconsistent with a small increase in risk. Our data provide additional evidence that alcohol intake is unlikely to have anything other than a very small effect on risk of EOC