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Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic
Elena Pereira1, Olga Camacho-Vanegas2, Sanya Anand2
1Department of Obstetrics, Gynecology and Reproductive Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Background:
High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.
Methods And Findings:
Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.
Conclusions:
Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers.
Insights
Personalized circulating tumor DNA (ctDNA) offers a powerful new tool for monitoring gynecologic cancers. This biomarker can detect recurrence earlier than current methods and predict patient survival outcomes.
Area of Science:
- Oncology
- Genetics
- Biomarker Discovery
Background:
- High-grade serous ovarian and endometrial cancers are highly lethal, with frequent recurrence after initial treatment.
- Current surveillance methods and biomarkers cannot reliably predict patient outcomes.
- Occult disease detection remains a challenge in managing these aggressive gynecologic cancers.
Purpose of the Study:
- To explore personalized circulating tumor DNA (ctDNA) as a surveillance and prognostic biomarker in gynecologic cancers.
- To compare the efficacy of ctDNA markers against current FDA-approved surveillance tools.
- To assess ctDNA's ability to detect residual disease and predict treatment response.
Main Methods:
- Collected tumor and serum samples from 44 patients with gynecologic cancers.
- Identified patient/tumor-specific mutations using whole-exome and targeted gene sequencing.
- Quantified ctDNA levels using droplet digital PCR and compared with CA-125 and CT scans.
Main Results:
- ctDNA was detected in 93.8% of patients.
- ctDNA levels correlated with CA-125 and CT scan results.
- ctDNA detected cancer when CT scans were negative, with a 7-month lead time on average.
- Undetectable ctDNA at six months post-treatment significantly improved progression-free and overall survival.
Conclusions:
- Personalized ctDNA biomarkers can identify residual disease and dynamically predict treatment response in gynecologic cancers.
- ctDNA serves as an independent predictor of survival in ovarian and endometrial cancers.
- Earlier detection of disease via ctDNA surveillance may improve survival and quality of life.

