High-Sensitivity Mutation Analysis of Cell-Free DNA for Disease Monitoring in Endometrial Cancer

This article is featured in Highlights of This Issue, p. 297

Endometrial cancer is the fourth most common female malignancy in the United States with more than 65,000 new cases estimated in 2022 (1). Despite advances in therapy, over the course of 2013–2017, uterine cancer death rates have increased more than any other type of cancer among women (2), and when compared with 1975, the overall 5-year relative survival for endometrial cancer has decreased (3). Endometrial cancer is histologically, clinically, and molecularly heterogeneous (4). The majority of low-risk histology, early-stage disease can be treated with primary surgery and carries a favorable prognosis (5), whereas serous carcinomas and carcinosarcomas, representing only about 15% of all endometrial cancers, account for the majority of deaths. In these high-risk endometrial cancers, the efficacy of standard therapeutic regimens (i.e., paclitaxel/carboplatin; refs. 6, 7), is limited, and novel targeted therapies are emerging (8). Other than radiologic imaging and serum CA125 level assessment in some patients, currently there is no noninvasive form of treatment response or disease progression monitoring available for patients with endometrial cancer.

Sequencing analysis of cell-free DNA (cfDNA) has emerged as a potential biomarker for early cancer detection, diagnosis, disease monitoring, and prognostication (9–11), and has been well studied in patients with early and advanced disease in a number of cancer types, including breast, colorectal, and lung cancer (12–14). Unlike those solid tumors, distant metastatic disease in endometrial cancer is not common (approximately 4%; ref. 15). To date, the role of cfDNA sequencing analysis in women with endometrial cancer is less defined. Small gene panels assessed by digital or quantitative PCR have identified circulating cell-free tumor (ct)DNA in subsets of patients with endometrial cancer, often those with high-risk disease (16–21); these studies were retrospective, however, and only provided limited longitudinal information. Next-generation sequencing (NGS) of hotspot amplicons of CTNNB1, KRAS, PTEN, and PIK3CA in plasma sampled at hysterectomy from patients with endometrioid endometrial cancer revealed mutations in 33% of patients, and found to be associated with advanced stage, deep myometrial/vascular invasion, and primary tumor size (22).

In this proof-of-principle study, we sought to define whether (i) the presence of cfDNA is associated with the histologic subtype or disease stage in patients with newly diagnosed endometrial cancer, (ii) whether sequencing analysis of longitudinal cfDNA samples can be used for disease monitoring in this disease, and (iii) whether the presence of ctDNA in plasma derived from patients with endometrial cancer is associated with disease progression or recurrence. To address these aims, we performed a retrospective analysis of prospectively collected plasma samples from patients with newly diagnosed endometrial cancer using a high-sensitivity NGS-based mutation profiling assay.

In this prospective proof-of-principle study, 44 biopsy-confirmed patients with newly diagnosed endometrial cancer consented to an institutional research protocol between September 2017 and July 2018 were included (Supplementary Fig. S1, Consort Diagram). Rather than a consecutive series, cases representative of all histologic types and FIGO stages were included to assess the presence of mutations in cfDNA according to histologic type and stage. All surgical specimens were subjected to central pathology review by a dedicated gynecologic pathologist (Lora H. Ellenson) to (i) define the histologic type following the World Health Organization of Female Genital Tumors (23), (ii) assess lymphovascular invasion, (iii) confirm the presence of isolated tumor cells (ITC) in the lymph nodes, and (iv) confirm the FIGO staging. Clinical data, including demographic information, surgical staging, chemotherapy, radiation treatment, imaging, and follow-up were extracted from the electronic medical records from the date of patient consent. This study was approved by Memorial Sloan Kettering Cancer Center's (MSK) institutional review board, and written informed consent was obtained from all patients. This study was conducted in accordance with the Declaration of Helsinki.

Peripheral blood samples were collected from each patient in two Streck Cell-Free DNA Blood Collection Tubes (Streck, La Vista, NE). Samples were collected prior to surgery, at the postoperative visit (median 22 days postsurgery, range 9–57 days), and at 6, 12, 18, and 24 months. Blood was processed and cfDNA extracted using the QIAsymphony SP system (Qiagen), quantified, and stored following validated standard operating procedures at MSK's cfDNA extraction laboratory in the Department of Pathology and Laboratory Medicine, as previously described (24).

Pretreatment MRI scans were obtained on a 3 Tesla magnet (GE Healthcare, Chicago, IL) in accordance with guidance from the European Society of Urogenital Radiology (ESUR; 25). A board-certified radiologist (Y. Lakhman) reviewed all MR images for the presence of tumor and, if present, assigned a preliminary MRI-based FIGO stage following the FIGO classification system, and according to the rules laid out in the ESUR guidelines (25, 26). Briefly, tumor was considered present if MR images demonstrated an intermediate T2 signal intensity (SI) lesion with diffusion restriction (high SI on high b-value DWI and low SI on ADC map), and hypoenhancement compared with myometrium on later phase DCE. The MRI-based FIGO stages are detailed in the Supplementary Methods. In addition to the above qualitative evaluation, two radiologists (J. Nincevic and Y. Lakhman) manually segmented every lesion on each tumor-containing slice using AquariusNet (Terarecon, Foster City, California) to automatically generate total tumor volume for each patient.

Primary endometrial cancers underwent clinical tumor-normal targeted DNA NGS of 468 cancer-related genes using MSK-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT; refs. 27, 28). NGS was performed on the primary tumor specimen in all but one case; for CD23, NGS was performed on a diagnostic biopsy (Supplementary Table S1). In addition, DNA was extracted from microdissected extrauterine tumor sites from 6 cases who presented with stage III or stage IV disease and subjected separately to MSK-IMPACT sequencing at MSK's Integrated Genomics Operation, as described (29). The median depth of coverage for tumor samples was 618x (range 101x–1030x) and for normal samples was 504x (range 325x–729x). MSK-IMPACT sequencing data were analyzed using previously described bioinformatics approaches (27, 30). Somatic mutations identified in the primary tumor or extrauterine site from a given patient were interrogated in the matched respective primary tumor/extrauterine site by manual inspection of BAM files using mpileup files (SAMtools mpileup; v1.2 htslib 1.2.1; SAMTOOLS, RRID:SCR_002105; ref. 31), as previously described (30). Primary endometrial cancers were stratified into The Cancer Genome Atlas molecular subtypes (32), as previously described (28).

For each patient, cfDNA obtained at baseline and postsurgery was subjected to MSK-Analysis of Circulating cfDNA to Examine Somatic Status (MSK-ACCESS), a high-depth NGS assay with molecular barcoding technology for the detection of very low frequency somatic alterations in 129 genes, a subset of the 468 MSK-IMPACT genes (33). Of the 44 endometrial cancers, 36 had a pre- and/or postoperative blood draw and the required plasma cfDNA input of 10 to 20ng cfDNA for MSK-ACCESS sequencing (Supplementary Fig. S1; Supplementary Table S1). In addition, longitudinal cfDNA samples from 25 patients with sufficient cfDNA and/or detectable mutations at baseline or postsurgery and/or disease progression were also subjected to MSK-ACCESS sequencing (Supplementary Table S1). cfDNA samples were sequenced to a median raw coverage of 25,611x (range 13,295–58,743x); post collapsing, the median duplex coverage was 1,340x (range 212x–2,839x). MSK-ACCESS raw sequence data were demultiplexed and processed as previously described (ref. 33; Supplementary Methods). Variant calling was performed in a matched tumor-informed manner (“genotyping”) using Waltz (https://github.com/mskcc/Waltz), and required at least 2 duplex consensus reads, comprising both strands of DNA, to call a somatic single-nucleotide variant (SNV) or short insertion and deletion (indel) at a site known to be altered in the matched tumor sample from a given patient, as previously described (33). Mutation-specific ctDNA fraction values were computed for all somatic mutations determined to be clonal in the tissue sample using MSK-IMPACT and covered in the MSK-ACCESS liquid biopsy panel (Supplementary Methods).

Comparisons between cfDNA concentrations and clinicopathologic parameters were performed using the Wilcoxon rank sum test. Progression-free survival (PFS) was defined from the date of surgery to the time of recurrence/progression or death or last follow-up whichever occurred first. The median PFS and PFS rates were estimated applying the Kaplan–Meier method. The association between somatic mutation in pre- and postsurgery cfDNA with PFS was examined using log-rank test with permutation (34). To accommodate the time dependent nature of postsurgery cfDNA mutation, a landmark analysis was performed using the landmark time of 51 days (or 1.68 months) which is the longest time interval between surgery date and postsurgery cfDNA measurement date in this cohort. A P value < 0.05 was considered statistically significant. All statistical analyses were performed using R version 4.1.1 (https://cran.r-project.org/; CRAN, RRID:SCR_003005).

Clinicopathologic information and the somatic mutations identified in the primary tumors and cfDNA are available in Supplementary Tables S1-S3. Targeted sequencing data that support the findings of this study is available at cBioPortal [www.cbioportal.org; Endometrial Carcinoma cfDNA (MSK, Clin Cancer Res 2022)].

In this study, 77% (34/44) of patients with endometrial cancer had FIGO stage I disease and 23% (10/44) had advanced-stage disease at diagnosis (stages III and IV; Table 1). As expected, endometrial cancers of endometrioid histology were the most common (24/44, 55%), followed by serous carcinoma (7/44; 16%) and carcinosarcoma (6/44; 14%; Table 1). All but 1 patient with endometrial cancer underwent primary surgery; half of the patients (21/43; 49%) received no further treatment, and the remaining patients were treated with either radiation and/or chemotherapy following surgery (Supplementary Table S1). Despite a subset of the 18- and 24-month timepoints occurring during the COVID-19 pandemic, 229 of the intended 258 (89%) longitudinal blood draws were collected. Median length of clinical follow-up was 33 months (range 0.3–44), with 11 patients being diagnosed with recurrent or persistent disease (Supplementary Table S1).

Median cfDNA concentration in preoperative cfDNA samples across cases was 2.71 ng/mL (range 0.66–20.62; Supplementary Table S1). We found patients with endometrial cancer with stage III/IV disease at diagnosis to have significantly higher amounts of cfDNA compared with those with stage I disease (Wilcoxon rank sum test, P = 0.028; Fig. 1A). In addition to surgical stage, MRI stage (25) was assigned on the basis of a preoperative MRI in 34/44 (77%) patients, which aligned with final surgical stage in 29/34 patients (Table 1, Supplementary Table S1). cfDNA concentrations were found to be numerically higher in histologic types associated with an aggressive clinical behavior, including carcinosarcoma and high-grade carcinomas of no specific type, however this association was not statistically significant likely due to the small sample size in some of the groups (P > 0.1; Fig. 1B).

The primary endometrial cancers of 42 patients were subjected to clinical tumor-normal FDA-authorized MSK-IMPACT sequencing of 468 cancer-related genes; for two cases there was no/insufficient tumor for molecular profiling (Supplementary Fig. S1). A median of 7.5 non-synonymous mutations were detected (range 1–92; Supplementary Table S2). Consistent with previous reports (32), the most commonly mutated genes were TP53 (52%), PTEN (50%), PIK3CA (50%), ARID1A (36%), and FBXW7 (29%; Fig. 1C; Supplementary Table S2). Of all 42 cases included, 10 endometrial cancers (24%) were of microsatellite instable (MSI) molecular subtype, 12 (29%) of copy number–low molecular subtype and 20 (48%) of copy number–high molecular subtype (Fig. 1C). Of the 23 endometrioid endometrial cancers, 11 (48%) were of copy number–low, 9 (39%) of MSI, and 3 (13%) of copy number–high molecular subtype (Fig. 1C).

We next sought to define whether the landscape of somatic mutations in baseline/preoperative cfDNA would be representative of that identified in the respective primary endometrial cancer. A high-depth UMI-based sequencing assay (MSK-ACCESS) revealed the baseline presence of tumor-derived mutations in cfDNA in eight of 36 cases subjected to MSK-ACCESS sequencing (22%), six of which had stage III or stage IV disease (Fig. 2; Supplementary Figures S1 and S2, Supplementary Table S1). ctDNA was also detected in a stage 1A high-grade adenosarcoma and a stage 1B high-grade mixed endometrioid/serous carcinoma with ITCs and lymphovascular space invasion (LVSI; Fig. 2; Supplementary Fig. S2), however none of the patients with low-grade stage I endometrioid endometrial cancer had detectable mutations in their preoperative cfDNA. Of these 8 endometrial cancers with ctDNA being present in plasma at baseline, 6 displayed LVSI, which was not significantly different from endometrial cancers without detectable ctDNA at baseline (5/25; Fisher exact test, P = 0.137; Supplementary Table S1). When defining the cancer cell fractions of the mutations identified (i.e., bioinformatically inferred percentage of tumor cells harboring the mutation in a given sample), we observed that all mutations that were clonal in the primary tumor and present in the MSK-ACCESS assay were also detected in baseline/preoperative cfDNA (Fig. 2; Supplementary Fig. S2). The only exception was case CD28, a stage IB mixed endometrial cancer with ITCs, where a clonal CDKN2A E61Pfs*54 and a TERT promoter C228T mutation present in the primary tumor were not detected in the plasma at baseline, but were detected at later time points (see below), whereas a subclonal TP53 mutation was (Fig. 2; Supplementary Fig. S2).

In four stage III/IV cases (i.e., CD20, CD22, CD26 and CD36) with detectable mutations in the cfDNA at baseline, in addition to the primary endometrial cancer, DNA from extrauterine sites, including (sentinel) lymph nodes, peritoneal implants and fallopian tube, was extracted and subjected to MSK-IMPACT sequencing. Heterogeneity between the primary tumor and extrauterine sites was observed, with mutations identified in the primary endometrial cancer not being present in the respective lymph nodes, whereas some lymph nodes/peritoneal implants harbored additional mutations that were not detected in the respective primary lesions (Supplementary Fig. S2). In case CD20, the primary tumor, the left exterior iliac sentinel lymph node (SLN) and obturator SLN shared a set of mutations, including an ARID1A truncating mutation and PIK3CA and KRAS hotspot mutations that were subclonal in the primary tumor but were found to become clonal in the SLNs (Fig. 2; Supplementary Fig. S2). A clonal PTEN mutation and RNF43, TSC1 and SMARCA4 frameshift mutations were, however, only shared between the primary endometrial cancer and left exterior iliac SLN but were absent in the obturator SLN. In turn, AGO2 and FOXA1 missense mutations were restricted to the two SLNs. In case CD22, the primary endometrial cancer and the mesenteric implant and three (sentinel) lymph nodes shared hotspot PIK3CA, TP53 and PPP2R1A mutations. An ARID1A truncating mutation was present in the primary lesion and three of the four extrauterine sites as well as in cfDNA (Fig. 2; Supplementary Fig. S2). Whereas the primary endometrial cancer and the fallopian tube lesion of case CD36 shared all somatic mutations identified, in case CD26, while FBXW7, NTRK3 and PIK3CA mutations were shared between all sites and cfDNA, a different PIK3CA hotspot mutation and a TP53 splice site mutation were restricted to the primary tumor. All mutations, however, were detected in the presurgery cfDNA. Sequencing analysis of the liquid biopsy at baseline was generally more representative of the repertoire of somatic mutation in the primary endometrial cancer than that of the (sentinel) lymph nodes (Fig. 2).

The ctDNA fraction in plasma obtained at baseline varied and was between 0.7% and 2.0% in the majority of cases (i.e., CD11, CD20, CD26, CD28, CD36, and CD37; Fig. 2; Supplementary Table S3). The ctDNA fraction in preoperative plasma was elevated in two cases, however. In CD22, a stage IVB endometrial serous carcinoma, the ctDNA fraction was 5.8%, and in CD23, a stage IVB carcinosarcoma with a very high tumor burden (2,608 cm³) the ctDNA fraction was 74.6%; both patients died from their disease 31 and 30 months after the baseline sample, respectively (Fig. 2; Supplementary Tables S1 and S3).

Next, we sought to define whether cfDNA sequencing of serial plasma DNA samples could be employed for disease monitoring including the assessment of treatment response and identification of early disease recurrence. For this, blood samples were collected every 6 months during follow-up; for 25 patients with either recurrent disease and/or detectable postsurgery ctDNA in plasma, the longitudinal cfDNA samples were subjected to MSK-ACCESS sequencing. In 6 of these 25 patients with endometrial cancer (24%), ctDNA was detected in the serial blood samples (Supplementary Table S1). The change in the mutant allele fraction (MAF) of the mutations identified as well as of the ctDNA fraction during follow-up closely followed disease progression and therapy response (Figs. 3–5; Supplementary Figures S3 and S4).

In case CD20, a stage IIIC2 dedifferentiated carcinoma, a marked increase in the MAFs was observed following the second course of chemotherapy (i.e., 8–9 months post diagnosis). Imaging at that time revealed increased pelvic, supraclavicular and thoracic lymph nodes (Fig. 3A). The overall ctDNA fraction and the allele fractions of the 10 mutations detected in plasma decreased during another course of chemotherapy and a clinical response with decreased size of lymph nodes was observed at 18 months. Mirroring the steep increase in MAFs/ctDNA fraction between 18 and 24 months, imaging at 24 months revealed increased metastatic retroperitoneal adenopathy throughout (Fig. 3A). Similarly, in case CD26, a stage IIIC1 carcinosarcoma, tumor was cleared during radiation and chemotherapy postsurgery with almost undetectable levels of tumor mutations in cfDNA at 6 months. Following chemotherapy, at the 12 months blood draw, a marked increase in the MAFs of all five mutations detected in the cfDNA, including two PIK3CA and a TP53 mutation, was observed, which was consistent with the increased tumor burden observed in this patient, including increase in lymph node sizes at 13 months and multiple spinal metastases at 15 months (Fig. 3B).

In patient CD22, a stage IVB serous carcinoma, a sharp reduction in the MAFs of all four somatic mutations (i.e., ARID1A, PIK3CA, TP53, and PPP2R1A mutations) was detected postsurgery and chemotherapy. At 12 months, ctDNA levels increased, consistent with new lung nodules and increased perirectal metastases observed by imaging (Fig. 4A). Despite the administration of 3 courses of chemotherapy over the next 12 months, the levels of ctDNA continued to rise; this lack of response aligned with the imaging data, which showed an increase in tumor burden and new splenic nodules (Fig. 4A; Supplementary Fig. S3). In case CD28, a stage IB grade 3 mixed endometrioid/serous carcinoma with ITCs, only 3 of the 5 mutations (i.e., two PTEN and a TP53 mutation) present in the primary tumor were detected in ctDNA at baseline (Fig. 2). Following the first course of chemotherapy plus radiation, an increase in the ctDNA fraction was observed. At 6 months, also the TERT promoter mutation and CDKN2A p.E61Pfs*54 mutation not detected at baseline were now identified in plasma, whereas there was no evidence of disease by imaging (Fig. 4B). A sharp increase in MAFs was observed for 6 months before the detection of new pulmonary nodules on imaging at 12 months. Also in patient CD28 the MAFs of the mutations kept rising despite additional courses of chemotherapy and radiation (Fig. 4B). This lack of response to chemo/radiation therapy was also found in the imaging studies, which showed increased disease volume and new distant metastases at 12, 18, and 24 months (Fig. 4B; Supplementary Fig. S3). Whilst all five primary tumor mutations (i.e., FBXW7, PIK3R1, APC, PTEN, and ERBB3 mutations) were identified in plasma at baseline in CD36, a patient with stage IIIA grade 1 endometrioid endometrial cancer, these remained undetectable following surgery and chemotherapy for 18 months, and the patient was rendered disease-free (Fig. 5A). We did observe an increase in the MAFs of the mutations at the 30-month blood draw, without any change in tumor burden on imaging until 36 months when the patient was noted to have an increased pelvic mass and sidewall nodule and underwent surgery for the removal of these lesions (Fig. 5A). Whilst exploratory and further studies would be required to confirm these findings, these data provide evidence demonstrating that the detection of ctDNA changes can provide a lead time over the radiologically and/or clinically detected recurrence in patients with endometrial cancer.

In contrast to ovarian cancer, the role of the tumor antigen CA125 for surveillance in endometrial cancer is less well established. For two of the endometrial cancers with detectable mutations in the cfDNA during follow-up, regular CA125 measurements were obtained. In both CD22 and CD28, elevated CA125 levels were detected, however only 5.8 months and 17 months after the increase in MAFs of tumor-derived mutations in cfDNA (Fig. 4A and B). This exploratory finding suggests that the detection of ctDNA in plasma may be more sensitive than the CA125 levels in serum of patients with endometrial cancer, warranting further studies.

We examined whether the detection of ctDNA at different time points would have the potential to predict recurrences in this series of newly diagnosed endometrial cancers. Of the 8 patients with detectable ctDNA mutations at baseline, all but one (CD37, adenosarcoma) recurred within the time of follow-up (median 33 months, range 0.3–44; Supplementary Table S1). The 4 patients with endometrial cancer with detectable mutations in cfDNA immediately postsurgery displayed recurrent or persistent disease following surgery (Supplementary Tables S1 and S3). Furthermore, for CD33, a stage IA carcinosarcoma, while no mutations were detected in the baseline/presurgery blood sample, we observed an increase in the MAFs of the mutations at 6 months, the only longitudinal sample, which mirrored the disease recurrence observed by imaging (Supplementary Fig. S4 and Supplementary Table S3). We found that the presence of ctDNA at baseline/preoperatively in this series of newly diagnosed endometrial cancers was significantly associated with PFS (P < 0.001; HR, 11.14; 95% confidence interval (CI), 2.72–45.59; Fig. 5B and C). Due to the limited number of events, a meaningful multivariate analysis could not be performed. Finally, we performed a landmark analysis showing that the detection of ctDNA immediately postsurgery also to be significantly associated with disease progression (P = 0.014; HR, 15.56; 95% CI, 2.16–112.16; Supplementary Fig. S5), however, the number of cases with measurable ctDNA after surgery in this cohort was small.

Our findings demonstrate that the amount of cfDNA present in plasma correlates with surgical stage in newly diagnosed patients with endometrial cancer, and that the detection of mutations in cfDNA using a high-sensitivity high-depth liquid biopsy sequencing assay was almost exclusively restricted to patients with endometrial cancer with advanced disease and more aggressive histology types. We have also shown that mutations detected in plasma/peripheral blood of patients with endometrial cancer are representative of those present in the primary tumor, with 35/38 (92%) of the primary tumor mutations identified in the cfDNA at diagnosis. Whilst there was limited genetic heterogeneity between the primary endometrial cancers and extrauterine sites/metastases analyzed by MSK-IMPACT sequencing, the mutations detected in cfDNA captured also those present in the extrauterine sites. Our study provides evidence that ctDNA detection is not only feasible in patients with endometrial cancer but also that ctDNA, levels closely mirror treatment response and disease progression. Finally, we demonstrate that the detection of mutations in cfDNA, both pre- and postsurgery, correlates with disease progression in women with newly diagnosed endometrial cancer.

Our study illustrates that even using a high-sensitivity high-depth UMI-based sequencing assay, ctDNA is detected only in a subset of patients with endometrial cancer and is associated with stage and histologic type (although not significant for histology, probably due to low numbers). Akin to other cancer types (35, 36), we found that cfDNA analysis may be useful in the setting of disease monitoring and detection of minimal residual disease (MRD) to predict disease recurrence. Furthermore, although we and others have previously shown that in early breast cancer serial sampling during follow-up was required for accurate MRD detection (14, 37–39), in endometrial cancer, the analysis of even a single blood sample taken before surgery offered information on disease recurrence. In contrast to breast or ovarian cancer, endometrial cancers are characterized by a high number of recurrently mutated cancer genes (4, 40). Therefore, sequencing panels targeting cancer-related genes rather than personalized tumor-specific assays are well suited for longitudinal cfDNA-based disease monitoring. At the individual mutation level, the MSK-ACCESS assay employed in this study detects through de novo and tumor-informed analysis high confidence mutations at 0.5% and 0.1%, respectively (33). With the ongoing development of assays for MRD detection following curative-intent treatment and during the surveillance period for relapse, which often target larger numbers of mutations and thereby increase sensitivity for ctDNA (11), future studies using ultrasensitive assays, in particular for patients with endometrial cancer with low-grade low-stage disease, are warranted.

Shedding of tumor DNA from cancer cells has been shown to be highly variable (12, 41), and the fraction of ctDNA in plasma in the endometrial cancers studied here was frequently undetectable in early-stage disease or low-grade histologies using a deep sequencing method. Endometrial cancers with high-risk histologic types, however, including carcinosarcoma and serous endometrial cancers, had higher ctDNA fractions in plasma. In addition to disease burden, these higher ctDNA fractions may be due to higher levels of processes that play a role in cfDNA release from cells such as proliferation, apoptosis, and necrosis (42).

Case CD37 included in this study was, following review of the resection specimen, an adenosarcoma rather than an endometrial carcinoma. The differential diagnosis of adenosarcoma includes benign and malignant endometrial conditions, including carcinosarcomas, and the clinical presentation may mimic that of endometrial cancer with abnormal uterine bleeding (43). Uterine adenosarcomas are a genetically heterogeneous group, and recurrent DICER1, FGFR2, and TP53 mutations, MDM2/CDK4/HMGA2 and TERT amplification as well as NCOA2/3 gene fusions, amongst others, have been reported in these tumors (43, 44). The primary adenosarcoma CD37 in this study was found to harbor 12 somatic mutations, including pathogenic DICER1, FGFR2, PTEN, and ARID1A mutations (Supplementary Fig. S2). Notably, the 3 mutations covered by the MSK-ACCESS assay were detected in the cfDNA at baseline (Fig. 2), providing evidence to suggest that cfDNA analysis may be used at least for a subset of uterine sarcomas. The diagnostic performance of liquid biopsy in sarcoma in general has been reported to vary and to be dependent on tumor type (45). Larger studies to demonstrate the prognostic value and clinical utility of cfDNA assays in uterine sarcoma are warranted.

Our study has several limitations. Despite the prospective accrual of patients with endometrial cancer, the number of patients when stratified according to stage or histologic type is small, and PFS analyses are based on limited number of events. Furthermore, due to the COVID-19 pandemic, 11% of samples could not be collected during the follow-up period as initially planned. Nevertheless, our findings provide a proof-of-principle of the role of cfDNA detection in prognostication and disease monitoring in endometrial cancer.

It is currently still unclear which patients with early-stage endometrial cancer would benefit from adjuvant therapy after surgery with radiation, chemotherapy or both (6, 46–48). In addition, recurrent endometrial cancer can still be cured with salvage therapy if it is caught before widespread metastasis occurs (49). Currently, the role of ITCs in the evaluation of risk of recurrence in endometrial cancer is also unanswered (50). Given these challenges, cfDNA analysis could benefit not only those patients with endometrial cancer with advanced disease for early detection of recurrence but could also prevent women the unnecessary morbidity of adjuvant therapy. On the basis of our findings, larger, prospective studies are warranted to incorporate cfDNA analysis as a monitoring tool and to guide additional therapies in patients with endometrial cancer at high risk for recurrence.

In conclusion, we have shown here that ctDNA mutation detection in plasma from patients with newly diagnosed endometrial cancer is not only feasible but has prognostic value and enables disease and treatment response monitoring.

J. Patel reports a patent for Systems and Methods for Detecting Cancer via cfDNA Screening pending. Y. Lakhman reports grants from the NIH/NCI Cancer Center (Support Grant P30 CA008748) during the conduct of the study as well as personal fees from Calyx and other support from Y-mAbs outside the submitted work. M.F. Berger reports personal fees from Eli Lilly and AstraZeneca outside the submitted work; in addition, M.F. Berger has a patent for Systems and Methods for Detecting Cancer via cfDNA Screening pending. D. Zamarin reports grants from NCI during the conduct of the study as well as grants and personal fees from Genentech, AstraZeneca, and Synthekine; grants from Plexxikon; personal fees from Memgen, Xencor, Targovax, Tessa Therapeutics, Agenus, Celldex, Crown Biosciences, GSK, Astellas, and Takeda; and other support from Immunos, Calidi Biotherapeutics, and Accurius outside the submitted work; in addition, D. Zamarin has a patent for Newcastle Disease Virus for cancer therapy licensed and with royalties paid from Merck. M.M. Leitao reports personal fees from Medtronic, Intuitive Surgical, Inc., and JnJ/Ethicon outside the submitted work. C.F. Friedman reports other support from Genentech and Merck and personal fees from Seagen and BMS outside the submitted work as well as research support to institution from AstraZeneca, Daiichi, Merck, BMS, Seagen, and Genentech/Roche. E. Jewell reports personal fees from Covidien/Medtronic outside the submitted work. J.S. Reis-Filho reports personal fees from Paige, Repare Therapeutics, Grupo Oncoclinicas, Roche Tissue Diagnostics, Novartis, MSD, Daiichi Sankyo, Personalis, and Eli Lilly outside the submitted work. C. Aghajanian reports grants from AbbVie, Clovis, Roche/Genentech, AstraZeneca, and GOG Foundation, Board of Directors and personal fees from Eisai/Merck, Mersana Therapeutics, Roche/Genentech, AbbVie, AstraZeneca/Merck, and Repare Therapeutics outside submitted work. N.R. Abu-Rustum reports grants from GRAIL outside the submitted work. K. Cadoo reports personal fees from AstraZeneca, MJH Life Sciences, MSD Ireland, GSK Ireland, and Nextcure; other support from MSD Ireland and Immunogen; and nonfinancial support from Pfizer and Roche Ireland outside the submitted work. B. Weigelt reports personal fees from Repare Therapeutics outside the submitted work. No disclosures were reported by the other authors.

C.W. Ashley: Conceptualization, data curation, formal analysis, supervision, validation, investigation, visualization, writing–original draft, writing–review and editing. P. Selenica: Data curation, formal analysis, investigation, writing–review and editing. J. Patel: Data curation, formal analysis, validation, writing–review and editing. M. Wu: Data curation, investigation, writing–review and editing. J. Nincevic: Investigation, writing–review and editing. Y. Lakhman: Investigation, writing–review and editing. Q. Zhou: Formal analysis, writing–review and editing. R.H. Shah: Formal analysis, writing–review and editing. M.F. Berger: Supervision, investigation, writing–review and editing. A. Da Cruz Paula: Investigation, writing–review and editing. D.N. Brown: Formal analysis, writing–review and editing. A. Marra: Investigation, visualization, writing–review and editing. A. Iasonos: Formal analysis, writing–review and editing. A. Momeni-Boroujeni: Investigation, writing–review and editing. K.M. Alektiar: Resources, writing–review and editing. K. Long Roche: Resources, writing–review and editing. O. Zivanovic: Resources, writing–review and editing. J.J. Mueller: Resources, writing–review and editing. D. Zamarin: Resources, writing–review and editing. V.A. Broach: Resources, writing–review and editing. Y. Sonoda: Resources, writing–review and editing. M.M. Leitao Jr: Resources, writing–review and editing. C.F. Friedman: Resources, writing–review and editing. E. Jewell: Resources, writing–review and editing. J.S. Reis-Filho: Conceptualization, investigation, writing–review and editing. L.H. Ellenson: Investigation, writing–review and editing. C. Aghajanian: Resources, funding acquisition, writing–review and editing. N.R. Abu-Rustum: Conceptualization, resources, funding acquisition, writing–review and editing. K. Cadoo: Conceptualization, investigation, writing–review and editing. B. Weigelt: Conceptualization, data curation, supervision, investigation, visualization, writing–original draft, writing–review and editing.

Research reported in this publication was supported in part by a Cancer Center Support Grant of the NIH/NCI (Grant no. P30CA008748). B. Weigelt and J.S. Reis-Filho are funded in part by Breast Cancer Research Foundation and by NCI/NIH (P50 CA247749 01) grants. B. Weigelt is also funded in part by Cycle for Survival grants.

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