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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 for the differentiation of women with benign pelvic masses from those with malignant pelvic masses using mRNA markers extracted from CTCs isolated from whole blood. Multiple serum tumor markers and mRNA markers will be measured, and the results will be compared to the actual clinical diagnosis made for each patient through other recognized methods (e.g. histopathology). The blood samples collected in the course of this study will be used to finalize the selection of mRNA and/or serum tumor markers to be evaluated in future prospective studies.
Exploratory Objective: Use statistical modeling to determine the need for and/or preliminary design of a mathematical algorithm to combine the multiple serum tumor and/or mRNA markers for estimation of the risk of ovarian cancer.
Full description
This study is exploratory in nature and is designed to be hypothesis generating to support the design of future studies. A total of 200 women diagnosed with a pelvic mass (defined as a simple, complex or a solid ovarian cyst / pelvic mass) who are scheduled for a laparotomy or laparoscopy for removal of the pelvic mass will be enrolled for evaluation of the primary and exploratory endpoints. An initial evaluation of the data will be conducted after identification of 15 evaluable subjects with histopathologically confirmed ovarian cancer. It is estimated that 50 - 100 subjects will be required to obtain a minimum of 15 evaluable subjects with histopathologically confirmed ovarian cancer. The remainder of the women enrolled (expected to be ~100 - 150 subjects) will be used to verify the findings from the initial evaluation (i.e. correlation of the markers with the absence or presence of malignancy) and to refine the assay/algorithm.
Within 60 days prior to surgery, 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 60 days prior to, or on the day of the pelvic mass surgery, collect up to 35mL of peripheral blood into one 5mL SST tube, which must be drawn first, followed by three separate 10mL EDTA tubes. Serum from SST tube will be prepared at the local study center and used for protein biomarker testing. The EDTA tubes will be shipped to the Medical University of Vienna, where the blood will be pooled and equal volumes processed using two different separation methods on the Parsortix™ system to capture and harvest rare cells. The harvested material from the EDTA tubes will be lysed, and total RNA will be extracted from the cell lysate for evaluation of multiple gene targets using quantitative PCR (qPCR).
Laparotomy or laparoscopy for removal 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 and grade of ovarian cancer where disease is identified.
Subjects will be considered negative for ovarian cancer:
Subjects will be considered positive for ovarian cancer:
For the purposes of enrollment, subjects diagnosed with a malignancy other than an ovarian cancer as well as those diagnosed with low malignant potential (LMP) / borderline tumors will not be counted as an ovarian cancer. However, two separate analyses of the final study data will be conducted: one where subjects diagnosed with other cancers are excluded from the analysis of the primary endpoint and the subjects diagnosed with LMP / borderline tumors are classified as being negative for malignancy, and a second where subjects diagnosed with other cancers and those diagnosed with LMP / borderline tumors are classified as being positive for malignancy.
Demographical and clinical data may be summarized using descriptive statistics. Continuous variables may be summarized using the number of observations, mean, standard deviation, coefficient of variation, median, and range as appropriate. Categorical values may be summarized using the number of observations and percentages as appropriate.
The association of the markers (i.e. serum protein markers and mRNA markers) with the histopathological diagnosis will be assessed using appropriate statistical methods (e.g., logistic regression, analysis of variance [ANOVA], etc.), depending on the endpoints. Analyses may be performed within and between various histopathological diagnosis sub-groups. Other clinical covariates (such as imaging results and subject demographics) may also be included in the modeling.
An initial evaluation of the correlation of the markers with the histopathological diagnosis will be performed after the identification of 15 subjects with histopathologically verified ovarian cancer. The final cohort of patients will be used to verify the findings from the initial evaluation (i.e. correlation of the markers with the absence or presence of malignancy) and to refine the assay/algorithm. Bootstrap analyses may be utilized on the entire set of 200 subjects to finalize an assay/algorithm for further study.
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204 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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