Evaluation of Multiple Protein and Molecular Biomarkers to Estimate Risk of Cancer in Gynecology Patients Presenting With a Pelvic Mass.

Overview

ANGLE has developed the Parsortix™ Cell Separation System (Parsortix), an automated system capable of harvesting rare circulating cells for analysis from a sample of peripheral blood based on cellular size and deformability. In a small pilot study, scientists at the Medical University of Vienna demonstrated that measurement of a combination of mRNA markers extracted from CTCs captured using the Parsortix system could be used to identify women with ovarian cancer. This study is designed to provide specimens for optimization of an assay using clinical and biomarker information (i.e. demographics, imaging results and/or serum tumor markers) in combination with mRNA extracted from rare cells in the blood of women presenting with a pelvic mass for the detection of malignancy. Primary Objective: Optimization of an assay/algorithm for the differentiation of women with benign pelvic masses from those with malignant pelvic masses using clinical and biomarker information (i.e. demographics, imaging results and/or serum tumor markers) in combination with mRNA markers extracted from rare cells isolated from whole blood. Multiple serum protein markers and mRNA markers will be measured, and the results will be compared to the actual clinical diagnosis made for each subject through other recognized methods (i.e. histopathology). Statistical modeling will be used to combine the clinical information, serum protein markers and/or mRNA markers for estimation of the risk of malignancy. If successful, the resulting risk algorithm will be evaluated in future, appropriately powered, prospective studies. Exploratory Objective: Use statistical modeling to determine the need for and/or preliminary design of a mathematical algorithm to combine the clinical information, serum protein markers and/or mRNA markers for estimation of the risk of malignancy.

This study is exploratory in nature and is designed to be hypothesis generating to support the design of future studies. Women diagnosed with a pelvic mass (ovarian, uterine, retroperitoneal, etc.) who are scheduled for an imaging guided biopsy, surgical biopsy or surgical excision for evaluation of their pelvic mass. It is estimated that approximately 200 women will be enrolled for evaluation of the primary and exploratory endpoints. Enrollment into the study will continue beyond 200 women if necessary to obtain a minimum of 50 evaluable women with a histopathologically confirmed malignancy, including ovarian, fallopian, peritoneal, endometrial, cervical, etc. Within 60 days prior to the pelvic mass evaluation procedure, each subject must have a pelvic imaging study (e.g. ultrasound, CT scan, MRI, etc.) conducted and read to visualize the pelvic mass according to the current standard of care. Results of the pelvic imaging study(ies) will be recorded. Within 30 days prior to, or on the day of the pelvic mass evaluation procedure, collect up to 35mL of whole blood into one 5mL SST tube, which must be drawn first, followed by three separate 10mL EDTA tubes. Serum from SST tube will be used for protein biomarker testing. Blood from EDTA tubes will be pooled and processed on the Parsortix™ System to capture and harvest rare cells. The captured rare cells will be eluted (harvested) and lysed, and total RNA will be extracted from the cell lysate for evaluation of multiple gene targets. Imaging guided biopsy, surgical biopsy or surgical excision for evaluation of the pelvic mass will be performed by a qualified individual. Tissue samples will be sent to the local pathology department for histological examination in accordance with standard institutional practices. Results of the histopathological evaluation will be recorded, including the final diagnosis along with histological sub-type, and if available, stage, of cancer where disease is identified. Where possible, representative fresh frozen tissue samples from the pelvic mass will be obtained for research purposes for evaluation of the same mRNA gene targets used in the cell harvests. Subjects will be considered negative for malignancy: * if the subject undergoes surgery and no mass is identified, or; * if the histopathological findings are negative for malignancy (i.e. benign conditions). Subjects will be considered positive for malignancy: * if the histological examination of the tissue taken at the time of the biopsy or surgery confirms the presence of a malignancy (i.e. ovarian, primary peritoneal, fallopian tube, endometrial, uterine, cervical, metastatic cancers, etc.). For the purposes of enrollment, subjects diagnosed with low malignant potential (LMP) / borderline tumors will be considered as benign (negative for malignancy). However, two separate analyses of the final study data will be conducted: one where subjects diagnosed with low malignant potential (LMP) / borderline tumors are classified as being negative for malignancy and a second time where these subjects are classified as being positive for malignancy. For subjects diagnosed with a malignancy, a bi-annual medical record review will be performed for up to 5 years after their enrollment into the study to collect information regarding their treatment response, chemotherapy sensitivity and resistance, time to recurrence, time to progression and overall survival. An algorithm for the prediction of benign vs. malignant disease will be constructed using the clinical information, serum biomarkers and mRNA markers. Additional analyses may be performed within and between various histopathological diagnosis sub-groups. The variable selection and algorithm construction will be done using various statistical methods, such as logistic regression, hierarchal clustering, classification and regression trees (CART), ROC curve evaluation, sensitivity/specificity analysis, visual plotting for determination of thresholds, etc. The inputs for evaluation may include continuous variables (e.g. age, ovary and dominant mass dimensions, serum biomarker results, mRNA expression levels, etc.), categorical variables (e.g. age groups, biomarker results by ranges, mRNA expression levels by ranges, etc.), and/or binary variables (e.g. presence or absence of particular risk factors and/or imaging features, age above or below a particular threshold, menopausal status, biomarker results above or below a particular threshold, mRNA expression levels above or below a particular threshold, etc.). A threshold for the resulting algorithm(s) output to differentiate between benign and malignant disease (or a subgroup thereof, such as epithelial ovarian cancer patients only) will be selected to optimize the sensitivity at a set specificity (e.g. maximize sensitivity at a minimum specificity level of \>80%). Upon completion of the long-term follow-up period, the association of the clinical data and markers with the subject's treatment response, chemotherapy sensitivity and resistance, time to recurrence, time to progression and overall survival will be assessed using the appropriate statistical methods (e.g. 2x2 tables, correlation analyses, Cox hazards regression, Kaplan-Meier plotting, etc.).