Liquid Biopsy-based Early Detection of Ovarian Cancer: a Proof-of-concept Study ( PROFOUND-OC )

A Multi-center, Perspective, Observational Case-control Study to Develop and Validate an Ovarian Cancer Early Detection Model Based on Peripheral Blood Multi-omic Analysis and Machine Learning

This study is a multi-center, observational study aiming at developing a machine learning-based early detection model using prospectively collected liquid biopsy samples from newly diagnosed ovarian cancer.

Peripheral blood samples from ovarian cancer (OC) patients will be prospectively collected to identify cancer-specific circulating signals by analyzing cell free DNA. Based on the comprehensive molecular profiling, a machine learning-driven noninvasive test will be trained and validated through a two-stage approach in clinically annotated individuals. Approximately 168 stage I-II OC patients will be enrolled in this study. Age-matched female controls included in model development were recruited in another study, which are volunteers without a cancer diagnosis after routine medical screening.

Inclusion Criteria:

• 40-75 years old
• Clinically and/or pathologically diagnosed ovarian cancer
• No prior or undergoing any systemic or local antitumor therapy, including but not limited to surgical resection, radiochemotherapy, endocrinotherapy, targeted therapy, immunotherapy, interventional therapy, etc.
• Able to provide a written informed consent and willing to comply with all part of the protocol procedures

Exclusion Criteria:

• Pregnancy or lactating women
• Known prior or current diagnosis of other types of malignancies comorbidities
• Severe acute infection (e.g. severe or critical COVID-19, sepsis, etc.) or febrile illness (body temperature of ≥ 38.0 °C) within 14 days prior to blood draw
• Recipients of organ transplant or prior bone marrow transplant or stem cell transplant
• Recipients of blood transfusion within 30 days prior to study blood draw
• Recipients of therapy in past 14 days prior to blood draw, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamine, hydrazine, arsenic trioxide
• Other conditions that the investigators considered are not suitable for the enrollment