Circulating tumor DNA to enhance detection of high-risk minimal residual disease in ovarian cancer relative to second look laparoscopy.
Abstract
5567 Background: Minimal residual disease (MRD) following frontline treatment of ovarian cancer has been established as a predictor of recurrence and survival. Historically, second look laparoscopy (SLL) has served as the gold-standard method to assess MRD; however the need for surgical evaluation limits widespread adoption and clinical applicability. Circulating tumor DNA (ctDNA) offers a non-invasive alternative for MRD detection and enables longitudinal monitoring with the potential for early identification of recurrence. Presently, the concordance between ctDNA-based detection and surgical assessment remains incompletely characterized. In this retrospective cohort study, we compare the predictive performance of ctDNA versus SLL for detecting clinically significant MRD after frontline treatment for high-grade ovarian cancer. Methods: This retrospective, single-institution study included patients with high-grade epithelial ovarian cancer who completed frontline chemotherapy and surgery. All patients underwent SLL to determine surgical MRD status. At the time of SLL, plasma was collected and profiled using NeXT Personal. Using whole-genome sequencing, this ultrasensitive, tumor-informed assay tracks up to 1,800 tumor-specific variants to detect ctDNA at levels down to ~1 part per million. Statistical analyses were conducted using RStudio (version 2026.01.0.392). Results: The cohort consisted of 72 patients (median follow up 38.9 months) with high-grade epithelial ovarian cancer, of whom 69 patients (95.8%) were in clinical remission by Ca-125 and imaging. Despite this, 30 patients (41.7%) were positive for MRD by ctDNA and 33 patients (45.8%) were positive for MRD by SLL. On multivariable analysis, ctDNA positivity independently predicted worse PFS (HR 4.35, 95% CI 2.17-8.72, p<0.001). The results of MRD and SLL were concordant in 53 (73.6%) of cases. There were 8 cases in which ctDNA was positive and SLL was negative. To date, 6/8 patients (75%) have recurred. There were 11 cases in which SLL was positive and ctDNA was negative. To date, 6/11 (54.5%) have recurred. Among these discordant cases, individuals with positive ctDNA but negative SLL had significantly worse PFS than cases with concordant negative results (HR 3.03, 95% CI 1.13-8.14, p=0.03). Whereas among cases with positive SLL and negative ctDNA, there was not a significant difference compared with concordant negative cases (HR 1.54, 95% CI 0.58-4.12, p=0.39). Conclusions: In this cohort where nearly all patients were in clinical remission, ctDNA was an independent predictor of PFS after frontline therapy in high-grade ovarian cancer. Although discordance occurs between ctDNA and SLL, these data suggest that ctDNA may detect clinically meaningful MRD not captured by SLL and could represent a more clinically relevant prognostic tool in this setting.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (20)
Helen D. Clark
The University of Texas MD Anderson Cancer Center, Houston, TX
Sanghoon Lee
Anne Knisely
Yi Chen
Kathleen Keough
Personalis, Inc., Menlo Park, CA
Charles Abbott
Personalis, Inc., Fremont, CA
Mario Tanguma
The University of Texas MD Anderson Cancer Center, Houston, TX
Pamela T. Soliman
Jeffrey Andrew How
The University of Texas MD Anderson Cancer Center, Houston, TX
Lois M. Ramondetta
The University of Texas MD Anderson Cancer Center, Houston, TX
Travis T. Sims
The University of Texas MD Anderson Cancer Center, Houston, TX
David M. Boruta
The University of Texas MD Anderson Cancer Center, Houston, TX
Shannon Neville Westin
The University of Texas MD Anderson Cancer Center, Houston, TX
Aaron Shafer
Roni Nitecki Wilke
The University of Texas MD Anderson Cancer Center, Houston, TX
Gwyn Richardson
The University of Texas MD Anderson Cancer Center, Houston, TX
Anil K. Sood
Sean Michael Boyle
Personalis, Inc., Fremont, CA
Richard Chen
Unibersity of Michigan, Ann Arbor, Michigan, United States
Amir A. Jazaeri