Role of cfDNA and ctDNA to improve the risk stratification and the disease follow-up in patients with endometrial cancer: towards the clinical application

Abstract

Background: There has been a rise in endometrial cancer (EC) incidence leading to increased mortality. To counter this trend, improving the stratification of post-surgery recurrence risk and anticipating disease relapse and treatment resistance is essential. Liquid biopsy analyses offer a promising tool for these clinical challenges, though the best strategy for applying them in EC must be defined. This study was designed to determine the value of cfDNA/ctDNA monitoring in improving the clinical management of patients with localized and recurrent disease.

Methods: Plasma samples and uterine aspirates (UA) from 198 EC patients were collected at surgery and over time. The genetic landscape of UAs was characterized using targeted sequencing. Total cfDNA was analyzed for ctDNA presence based on the UA mutational profile.

Results: High cfDNA levels and detectable ctDNA at baseline correlated with poor prognosis for DFS (p-value < 0.0001; HR = 9.25) and DSS (p-value < 0.0001; HR = 11.20). This remained clinically significant when stratifying tumors by histopathological risk factors. Of note, cfDNA/ctDNA analyses discriminated patients with early post-surgery relapse and the ctDNA kinetics served to identify patients undergoing relapse before any clinical evidence emerged.

Conclusions: This is the most comprehensive study on cfDNA/ctDNA characterization in EC, demonstrating its value in improving risk stratification and anticipating disease relapse in patients with localized disease. CtDNA kinetics assessment complements current strategies to monitor the disease evolution and the treatment response. Therefore, implementing cfDNA/ctDNA monitoring in clinical routines offers a unique opportunity to improve EC management.

Translational relevance: The study demonstrates that high levels of cfDNA and detectable ctDNA at baseline are strong indicators of poor prognosis. This enables more accurate risk stratification beyond traditional histopathological factors, allowing clinicians to identify high-risk patients who may benefit from more aggressive treatment and closer monitoring. Moreover, longitudinal analysis of cfDNA/ctDNA can detect disease recurrence months before clinical symptoms or imaging evidence appear. This early warning system offers a significant advantage in clinical practice, providing a window of opportunity for early intervention and potentially improving patient outcomes.

Keywords: Blood biomarkers; Endometrial cancer; Liquid Biopsy; Prognostic biomarkers; Tumour kinetics.

Fig. 1

Schematic representation of the cfDNA and ctDNA analyses in the cohort of endometrial cancer patients. Consort plot showing the number of patients excluded at each time point of the study

Fig. 2

The value of pre-surgery cfDNA in identifying patients with poor clinical outcome. A-J. Violin plots of the pre-surgery cfDNA levels (Log10 ng/mL) according to the clinicopathologic variables of the tumours. Statistical significance was evaluated by based on Mann–Whitney U test **p < 0.01. K. Classification of the patients as low or high pre-surgery cfDNA based on the optimal cut point (25 ng/mL). L-M. Kaplan Meier curves showing DFS (L) and DSS (M) based on pre-surgery cfDNA levels. Univariate Cox proportional-hazards model was used to estimate HR and log-rank test to report p-value

Fig. 3

The value of ctDNA analyses in endometrial cancer. A-J. Box plots showing the highest variant allelic frequency (VAF %) of the alterations found in the ctDNA accordingly the patient clinical variables. Statistical significance was assessed based on Mann–Whitney U test **p < 0.01, **p < 0.001, ****p < 0.0001. K. Percentage of patients with positive and negative ctDNA levels. L-M. Kaplan Meier curves showing DFS (L) and DSS (M) in patients with positive vs. negative levels of ctDNA. Univariate Cox proportional-hazard model was used to estimate HR and log-rank test to report p-value

Fig. 4

Combined analyses of cfDNA and ctDNA identify the patients with the worst clinical outcome. A-B. Kaplan Meier curves showing DFS (A) and DSS (B) in patients according to the pre-surgery high levels of cfDNA and detectable levels of ctDNA. C. Bar plot with the early recurrence status according to the combinatorial approach and the ESGO risk classification D. Graphical representation of the univariate (blue) and multivariate (red) Cox proportional-hazard models. P-value > 0.05 is represented with the *symbol. E-F. Kaplan-Meier curves showing DFS in patients according to the pre-surgery high levels of cfDNA and detectable levels of ctDNA in patients with low or intermediate (E) and high-intermediate or high (F) risk of recurrence based on the ESGO-ESTRO-ESP risk stratification

Fig. 5

Longitudinal analyses of cfDNA/ctDNA allow for early detection and accurately reflect the disease kinetics. A. Swimmer plot of the 18 patients that underwent tumour progression divided based on the combinatorial approach with longitudinal samples collected at least 6 months prior to the relapse (cfDNA and ctDNA). B-D. Example figures of the cfDNA (blue dotted line) and ctDNA kinetics (yellow line) in patients with advanced disease. (1) Radiotherapy, (2) Carboplatin-Paclitaxel, (3) Dostarlimab, (4) Exemestane, (5) Doxorrubicin and Avastin, (6) Lenvatinib and Pembrolizumab, (7) Topotecan and Bevacizumab