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

NCT02781272CompletedOBSERVATIONAL

Summary

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.

Key Facts

Lead Sponsor

Angle plc

Enrollment

200

Start Date

2016-06-30

Completion Date

2017-06-01

Study Type

OBSERVATIONAL

Official Title

ANG-003 EMBER Study: Evaluation of Multiple Protein and Molecular Biomarkers to Estimate Risk of Cancer in Gynecology Patients Presenting With a Pelvic Mass.

Interventions

Pelvic imagingBlood drawImaging guided biopsysurgical biopsy or surgical excision

Conditions

Ovarian Neoplasms

Eligibility

Age Range

18 Years+

Sex

FEMALE

Inclusion Criteria:

* Women \>18 years of age;
* Documented evidence of a pelvic mass by imaging;
* Selected to undergo biopsy, laparotomy or laparoscopy for pathologic evaluation of their pelvic mass;
* Willing and able to provide written informed consent.

Exclusion Criteria:

* Known pregnancy;
* Previous malignancy within the past 5 years, excluding skin cancers (squamous cell or basal cell);
* Unwilling or unable to follow protocol requirements or to provide informed consent.

Outcome Measures

Primary Outcomes

Histopathological diagnosis

Tissue samples taken from the pelvic mass will be evaluated in the URMC GYN pathology department according to institutional guidelines. Results from the histopathological evaluation, including the final diagnosis (i.e. benign, malignant, etc.), histopathology description, and, if malignant, clinical or surgical staging and tumor subtype, will be recorded.

Time frame: Within 30 days after biopsy or surgical procedure to evaluate pelvic mass

Presence or absence of circulating tumor cells

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.

Time frame: Up to 30 days prior to biopsy or surgical procedure to evaluate pelvic mass

Serum protein markers

Serum from SST tube will be used for protein biomarker testing.

Time frame: Up to 30 days prior to biopsy or surgical procedure to evaluate pelvic mass

Locations

University of Rochester Medical Center Wilmot Cancer Institute, Rochester, United States

Linked Diseases

Ovarian Neoplasms

Ovarian Neoplasms — a type of gynecological cancer.

Linked Papers

2022-09-07

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass

OBJECTIVE: To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood. METHODS: This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared. RESULTS: A total of 183 evaluable patients were enrolled (average age 56 years, range 19–91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0–98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2–65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9–93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3–97.8%) for stage I–II and 98.9% (95% CI 96.7–100%) for stage III–IV patients with epithelial ovarian cancer. CONCLUSION: Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02781272. FUNDING SOURCE: This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).