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. 2015 Dec 30;10(12):e0145754.
doi: 10.1371/journal.pone.0145754. eCollection 2015.

Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

Affiliations

Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

Elena Pereira et al. PLoS One. .

Abstract

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Overview of patient enrollment, clinical follow-up and personalized ctDNA analysis.
Fig 2
Fig 2. Circulating tumor DNA can detect relapse earlier than CA125 and CT scan imaging.
In this representative example, increases in ctDNA levels in Patient 137 levels precede a rise in CA-125 levels by six months and pre-date positive identification of tumor growth requiring bowel resection seven months later. CT scanning was non-specific and patient was brought to the operating room for exploratory surgery, which revealed the presence of tumor.
Fig 3
Fig 3. Undetectable levels of ctDNA following initial treatment are associated with improved survival.
Kaplan–Meier analysis of progression-free (left panel) and overall survival (right panel) between individuals with undetectable (ctDNA = 0; blue lines) and detectable ctDNA (≥ 1; red lines). Significant differences in progression-free survival (p = 0.001) and overall survival (p = 0.0194) between undetectable and detectable groups.

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Grants and funding

These studies were funded, in part, by donations from the Varadi Ovarian Initiative in Cancer Education (VOICE), the Derald H. Ruttenberg Foundation and the M.S. Gordon family. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.