Neoplasms

All Conditions

Skin and Connective Tissue Diseases

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Gland and Hormone Related Diseases

Rare Diseases

Carcinoma

Breast Neoplasms

Carcinoma in Situ

Ovarian Neoplasms

Carcinoma, Ovarian Epithelial

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Endocrine Gland Neoplasms

Ovarian Diseases

Adnexal Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Genital Neoplasms, Female

Urogenital Neoplasms

Endocrine System Diseases

Gonadal Disorders

Ovarian Cancer

Ovarian Epithelial Cancer

Herbal and Botanical

All Drugs and Chemicals

Kava

Procedure/Surgery: Lavage of the Cavum uteri and proximal Fallopian tubes, performed in the luteal phase of the female cycle

Speiser-catheter for uterine and tubal lavage

In Phase I the sponsor will systematically test conditions for lavage filtration that increase tumor cell fraction without reducing tumor mutation yield. The Sponsor will also transition all lavages to luteal phase timing, when endometrial shedding is least. In Phase II the Sponsor will examine our data in context of clinical characteristics, particularly age, to develop a multivariate model that determines optimal mutant allele frequency (MAF) diagnostic threshold by patient. Furthermore, the sponsor will explore a highly innovative idea, entailing empirically determining each individual's background mutation load, agnostic of the aging or mutagenic exposures responsible, and using this as a personalized calibrator to determine optimal MAF diagnostic threshold.

Case control study in two patient population (AIM 1 in average risk population, AIM 2 in high risk population)

Early Detection of High Grade Ovarian Cancer Using Uterine Lavage EHUD Study and Duplex Sequencing

Pilot Study of Early Detection of High Grade Ovarian Cancer Using Uterine Lavage and Duplex Sequencing

Preliminary testing with two samples indicated that filtration of UtLs to remove clusters of endometrial cells could increase sensitivity for tumor mutations several fold. This dataset will be expanded by analyzing the filtration effect in 10 ULs from patients with HGSC with known TP53 mutations. Each UtL will be divided in half: the first half will be filtered and the second will remain unfiltered. DNA will be extracted from the filtered, filtrate, and unfiltered fractions and analyzed by TP53KDS (total of 30 samples). For each UL, the DNA yield will be compared in each of the fractions and the MAF of the tumor mutation. It is anticipated that the filtered fraction will contain less DNA then the unfiltered fraction but the tumor mutation will be present at a higher frequency (i.e. more is gained by enrichment than is lost by reduction from less available DNA).

SNP allele fraction (AF) will be compared at different dilutions to determine accuracy (expected AF vs. observed AF), precision (AF variation among replicates), and lowest limit of detection achievable.

To asses the reproducibility in clinical use total mutation frequency will be assayed. The coefficient of variation among replicates will be calculated. Overall mutation frequency across TP53 in UtLs samples will be measured for both replicates of each patient. VAF will be approximated by number of non-reference duplex bases/total duplex bases sequenced. Confidence intervals will be computed using a binomial normal approximation.

A detailed mutation profile will be generated from the DS output files: mutant allele frequency (MAF) for all mutated positions, mutation spectrum, predicted pathogenicity to protein function, relationship to known hotspots, and overall mutation load (number of mutant nucleotides divided by the total number of nucleotides sequenced). Following this, samples will be unblinded for cases-controls status.

TP53 MAF from DNA collected by UtLs will be used as predictor for differentiating between average risk patients (AIM I) with and without HGSC by logistic regression modelling. An analogous analysis will be applied to the group of high risk patients (AIM II) where presence and absence of STIC is defining the outcome variable. Cut off values for mutant allele frequency will be suggested in both cases and specificity and sensitivity will be estimated including appropriate confidence intervals.

The association between TP53 mutation frequencies in uterine lavage and leukocytes will be examined and will determine whether false negatives in Aim 1A correspond to cases with increased BB in leukocytes. In addition, TP53 mutation frequencies in leukocytes will be analyzed as a predictor of case control status, again using the leave out 10% procedure. This innovative calibration method will be compared with the simple ROC metrics achieved with the univariate model using a fixed mutation fraction as well as the adjusted multivariate model developed based on other patient characteristics such as age. As a scientific question unrelated to the present aims, it is worth investigating whether leukocyte TP53 mutation load will serve as an independent predictor of patient age, overall health or history of mutagenic exposures.

Comparison of performance of UtL collection with that of Pap smear collection. It will be investigated if any additional power to discriminate cases from controls can be gained by combining information from Pap smears and ULs.

Aiming to evaluate the potential for defining a DNA-Methylation signature for simple PCR testing, dCT-PCR values from 96-plexed high-throughput MSREqPCR analysis will be analysed by bioinformatics \& biostatistics. See Detailed description og the Aim III above for more details.

Spots Global Cancer Trial Database for ovarian epithelial cancer f