Abnormal preoperative haematological parameters in Endometrial cancer; reflecting tumour aggressiveness or reduced response to radiotherapy?

BACKGROUND: In endometrial cancer (EC), preoperative anaemia, thrombocytosis and leucocytosis appear to be associated with worse prognosis. It remains unclear whether these parameters solely reflect tumour aggressiveness, or also impact response to adjuvant treatment. Therefore, our primary aim is to evaluate the prognostic relevance of anaemia, thrombocytosis and leucocytosis on survival in EC. Secondary, to explore their predictive relevance in response to radiotherapy in EC. METHODS: A retrospective multicentre cohort study was performed within 10 hospitals. Preoperative haematological parameters were defined as: Anaemia - haemoglobin <7.45 mmol/L (<12 g/Dl), thrombocytosis - platelets >400 × 109 platelets/L, leucocytosis - leukocytes >10 × 109/L. The relationship of haematological parameters with clinicopathological characteristics, ESGO/ESTRO/ESP risk groups and survival were evaluated. Furthermore, the predictive value of haematological parameters was determined on the overall response to adjuvant radiotherapy and for the ESGO/ESTRO/ESP intermediate-risk group solely receiving radiotherapy. RESULTS: A total of 894 patients were included with a median follow-up of 4.5 years. Anaemia was present in 103 (11.5%), thrombocytosis in 79 (8.8%) and leucocytosis in 114 (12.7%) patients. The presence of anaemia or thrombocytosis was significantly associated with ESGO/ESTRO/ESP high-risk (respectively, P = 0.002 and P = 0.041). In the entire cohort, anaemia remained independently associated with decreased disease-specific survival (HR 2.31, 95% CI (1.19-4.50), P = 0.013) after adjusting for age, the abnormal haematological parameters and ESGO/ESTRO/ESP risk groups. In patients that were treated with adjuvant radiotherapy (n = 239), anaemia was associated with significant reduced 5-year disease-specific and recurrence-free survival (P = 0.005 and P = 0.025, respectively). In ESGO/ESTRO/ESP intermediate risk patients that received solely vaginal brachytherapy (n = 74), anaemia was associated with reduced disease-specific survival (P = 0.041). CONCLUSIONS: Current data demonstrate the importance of preoperative anaemia as independent prognostic factor in patients with EC. Moreover, anaemia seems to be associated with reduced response to radiotherapy. Prospective validation in a larger study cohort is needed to verify anaemia as predictive biomarker for radiotherapy.What is already known on this subject? In endometrial cancer, preoperative abnormal haematological parameters like, anaemia, thrombocytosis and leucocytosis appears to be associated with FIGO advanced-stage and unfavourable outcome.What do the results of this study add? It remains unclear whether anaemia, thrombocytosis or leucocytosis solely reflecting worse prognosis by advanced tumour stage, or also impact response to adjuvant treatment. Current data demonstrate that anaemia is independent associated with decreased disease-specific survival and anaemia seems related with reduced response to radiotherapy and in specific to vaginal brachytherapy in ESGO/ESTRO/ESP intermediate risk patients.What are the implications of these findings for clinical practice and/or further research? Specific applied adjuvant treatment is needed if patients with anaemia have a reduced response to radiotherapy in EC. Prospective validation in a larger study cohort is required to verify anaemia as predictive biomarker for radiotherapy and to further evaluate the prognostic/predictive impact of anaemia in addition to the molecular subgroups.

In this study we focused on three specific blood values before surgery to predict survival outcomes in endometrial cancer patients: low haemoglobin (anaemia), high platelet count (thrombocytosis) and high white blood cell count (leucocytosis). We studied 894 patients with endometrial cancer over about 4.5 years, in which 11.5% had anaemia, 8.8% thrombocytosis and 12.7% leucocytosis. Anaemia was linked to a lower chance of surviving endometrial cancer, even after we considering patients' age, thrombocytosis, leucocytosis and the endometrial cancer risk classification groups. In patients who received radiotherapy after surgery (293 patients), anaemia was linked to a lower change of surviving and cancer coming back within 5 years. In patients within the intermediate endometrial cancer risk classification group who only received specific radiotherapy (74 patients), anaemia was even linked with lower chance of survival. In conclusion, anaemia is an important factor in predicting endometrial cancer outcomes, and it might also make radiotherapy less effective for some patients.

Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer.

Patients with high-grade endometrial carcinoma (EC) have an increased risk of tumor spread and lymph node metastasis (LNM). Preoperative imaging and CA125 can be used in work-up. As data on cancer antigen 125 (CA125) in high-grade EC are limited, we aimed to study primarily the predictive value of CA125, and secondarily the contributive value of computed tomography (CT) for advanced stage and LNM. Patients with high-grade EC (n = 333) and available preoperative CA125 were included retrospectively. The association of CA125 and CT findings with LNM was analyzed by logistic regression. Elevated CA125 ((>35 U/mL), (35.2% (68/193)) was significantly associated with stage III-IV disease (60.3% (41/68)) compared with normal CA125 (20.8% (26/125), [p < 0.001]), and with reduced disease-specific-(DSS) (p < 0.001) and overall survival (OS) (p < 0.001). The overall accuracy of predicting LNM by CT resulted in an area under the curve (AUC) of 0.623 (p < 0.001) independent of CA125. Stratification by CA125 resulted in an AUC of 0.484 (normal), and 0.660 (elevated). In multivariate analysis elevated CA125, non-endometrioid histology, pathological deep myometrial invasion ≥50%, and cervical involvement were significant predictors of LNM, whereas suspected LNM on CT was not. This shows that elevated CA125 is a relevant independent predictor of advanced stage and outcome specifically in high-grade EC.

Pure and mixed clear cell carcinoma of the endometrium: A molecular and immunohistochemical analysis study.

BACKGROUND: Uterine clear cell carcinoma (CCC) consists of either pure clear cell histology but can also display other histological components (mixed uterine CCCs). In this study, the molecular and immunohistochemical background of pure and mixed uterine CCC was compared. Secondly, it was evaluated whether histological classification and molecular background affected clinical outcome. METHODS: A retrospective multicenter study was performed comparing pure uterine CCCs (n = 22) and mixed uterine CCCs (n = 21). Targeted next-generation sequencing using a 12-gene targeted panel classified cases as polymerase-ε (POLE) mutated, microsatellite instable (MSI), TP53 wildtype or TP53 mutated. Immunohistochemistry was performed for estrogen receptor, progesterone receptor, L1 cell adhesion molecule, MSH6, and PMS2. RESULTS: The following molecular subgroups were identified for pure and mixed uterine CCCs, respectively: POLE mutated 0% (0/18) and 6% (1/18); MSI in 6% (1/18) and 50% (9/18); TP53 wildtype in 56% (10/18) and 22% (4/18); TP53 mutated in 39% (7/18) and 22% (4/18) (p = 0.013). Patients with mixed CCCs had improved outcome compared to patients with pure CCCs. Frequent TP53 mutations were found in pure CCCs and frequent MSI in mixed CCCs, associated with clinical outcome. CONCLUSION: Pure and mixed uterine CCCs are two entities with different clinical outcomes, which could be explained by different molecular backgrounds. These results underline the relevance of both morphological and molecular evaluation, and may assist in tailoring treatment.

Advancing the treatment of localized prostate cancer with MR-guided radiotherapy.

External beam radiotherapy (EBRT) is an important cornerstone in the treatment of localized prostate cancer. Current image-guided radiotherapy (IGRT) techniques allow for more accurate and precise delivery of radiation treatment by the use of imaging before each fraction. Magnetic resonance guided radiotherapy (MRgRT) is the next step in IGRT with hybrid systems combining linear accelerators with MRI-scanners. With MRgRT, it is possible to visualize pelvic anatomy in great detail and subsequently perform replanning of the radiation dose distribution before each radiotherapy fraction. This technique has the potential to increase the therapeutic window of EBRT, by improved normal tissue sparing due to margin reduction and more accurate target dose delivery. This is particularly promising for prostate cancer, with its biology lending itself to ultra-hypofractionation, reducing radiotherapy treatment to as little as five fractions. Also, recent studies have shown that focal dose escalation to the intraprostatic tumor to high ablative doses can substantially increase disease-free survival. In this article, we discuss these unique opportunities as well as the potential future benefits of MRgRT in prostate cancer treatment.

Improved preoperative risk stratification in endometrial carcinoma patients: external validation of the ENDORISK Bayesian network model in a large population-based case series.

PURPOSE: Preoperative risk stratification of newly diagnosed endometrial carcinoma (EC) patients has been hindered by only moderate prediction performance for many years. Recently ENDORISK, a Bayesian network model, showed high predictive performance. It was the aim of this study to validate ENDORISK by applying the model to a population-based case series of EC patients. METHODS: ENDORISK was applied to a retrospective cohort of women surgically treated for EC from 2003 to 2013. Prediction accuracy for LNM as well as 5-year DSS was investigated. The model's overall performance was quantified by the Brier score, discriminative performance by area under the curve (AUC). RESULTS: A complete dataset was evaluable from 247 patients. 78.1% cases were endometrioid histotype. The majority of patients (n = 156;63.2%) had stage IA disease. Overall, positive lymph nodes were found in 20 (8.1%) patients. Using ENDORISK predicted probabilities, most (n = 156;63.2%) patients have been assigned to low or very low risk group with a false-negative rate of 0.6%. AUC for LNM prediction was 0.851 [95% confidence interval (CI) 0.761-0.941] with a Brier score of 0.06. For 5-year DSS the AUC was 0.698 (95% CI 0.595-0.800) as Brier score has been calculated 0.09. CONCLUSIONS: We were able to successfully validate ENDORISK for prediction of LNM and 5-year DSS. Next steps will now have to focus on ENDORISK performance in daily clinical practice. In addition, incorporating TCGA-derived molecular subtypes will be of key importance for future extended use. This study may support further promoting of data-based decision-making tools for personalized treatment of EC.

Relevance of Molecular Profiling in Patients With Low-Grade Endometrial Cancer.

Importance: Patients with low-grade (ie, grade 1-2) endometrial cancer (EC) are characterized by their favorable prognosis compared with patients with high-grade (ie, grade 3) EC. With the implementation of molecular profiling, the prognostic relevance of tumor grading might lose attention. As most patients present with low-grade EC and have an excellent outcome, the value of molecular profiling for these patients is unclear. Objective: To determine the association of molecular profiling with outcomes among patients with low-grade EC. Design, Setting, and Participants: This retrospective cohort study included a multicenter international European cohort of patients diagnosed with EC between 1994 and 2018, with a median follow-up of 5.9 years. Molecular subgroups were determined by next-generation sequencing using single-molecule molecular inversion probes and by immunohistochemistry. Subsequently, tumors were classified as polymerase epsilon (POLE)-altered, microsatellite instable (MSI), tumor protein p53 (TP53)-altered, or no specific molecular profile (NSMP). Patients diagnosed with any histological subtypes and FIGO (International Federation of Gynecology and Obstetrics) stages of EC were included, but patients with early-stage EC (FIGO I-II) were only included if they had known lymph node status. Data were analyzed February 20 to June 16, 2022. Exposures: Molecular testing of the 4 molecular subgroups. Main Outcomes and Measures: The main outcome was disease-specific survival (DSS) within the molecular subgroups. Results: A total of 393 patients with EC were included, with a median (range) age of 64.0 (31.0-86.0) years and median (range) body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 29.1 (18.0-58.3). Most patients presented with early-stage (290 patients [73.8%]) and low-grade (209 patients [53.2%]) disease. Of all patients, 33 (8.4%) had POLE-altered EC, 78 (19.8%) had MSI EC, 72 (18.3%) had TP53-altered EC, and 210 (53.4%) had NSMP EC. Across all molecular subgroups, patients with low-grade EC had superior 5-year DSS compared with those with high-grade EC, varying between 90% to 100% vs 41% to 90% (P < .001). Multivariable analysis in the entire cohort including age, tumor grade, FIGO stage, lymphovascular space invasion, and the molecular subgroups as covariates found that only high-grade (hazard ratio [HR], 4.29; 95% CI, 2.15-8.53; P < .001), TP53-altered (HR, 1.76; 95% CI, 1.04-2.95; P = .03), and FIGO stage III or IV (HR, 4.26; 95% CI, 2.50-7.26; P < .001) disease were independently associated with reduced DSS. Conclusions and Relevance: This cohort study found that patients with low-grade EC had an excellent prognosis independent of molecular subgroup. These findings do not support routine molecular profiling in patients with low-grade EC, and they demonstrate the importance of primary diagnostic tumor grading and selective profiling in low-grade EC to increase cost-effectiveness.

Diagnostic accuracy of mutational analysis along the Müllerian tract to detect ovarian cancer.

OBJECTIVE: Ovarian cancer is known for its poor prognosis, which is mainly due to the lack of early symptoms and adequate screening options. In this study we evaluated whether mutational analysis in cervicovaginal and endometrial samples could assist in the detection of ovarian cancer. METHODS: In this prospective multicenter study, we included patients surgically treated for either (suspicion of) ovarian cancer or for a benign gynecological condition (control group). A cervicovaginal self-sample, a Papanicolaou (Pap) smear, a pipelle endometrial biopsy, and the surgical specimen were analyzed for (potentially) pathogenic variants in eight genes (ARID1A, CTNNB1, KRAS, MTOR, PIK3CA, POLE, PTEN, and TP53) using single-molecule molecular inversion probes. Sensitivity and specificity were calculated to assess diagnostic accuracy. RESULTS: Based on surgical histology, our dataset comprised 29 patients with ovarian cancer and 32 controls. In 83% of the patients with ovarian cancer, somatic (potentially) pathogenic variants could be detected in the final surgical specimen, of which 71% included at least a TP53 variant. In 52% of the ovarian cancer patients, such variants could be detected in either the self-sample, Pap smear, or pipelle. The Pap smear yielded the highest diagnostic accuracy with 26% sensitivity (95% CI 10% to 48%). Overall diagnostic accuracy was low and was not improved when including TP53 variants only. CONCLUSIONS: Mutational analysis in cervicovaginal and endometrial samples has limited accuracy in the detection of ovarian cancer. Future research with cytologic samples analyzed on methylation status or the vaginal microbiome may be relevant.

External validation study of endometrial cancer preoperative risk stratification model (ENDORISK).

Introduction: Among industrialized countries, endometrial cancer is a common malignancy with generally an excellent outcome. To personalize medicine, we ideally compile as much information as possible concerning patient prognosis prior to effecting an appropriate treatment decision. Endometrial cancer preoperative risk stratification (ENDORISK) is a machine learning-based computational Bayesian networks model that predicts lymph node metastasis and 5-year disease-specific survival potential with percentual probability. Our objective included validating ENDORISK effectiveness in our patient cohort, assessing its application in the current use of sentinel node biopsy, and verifying its accuracy in advanced stages. Methods: The ENDORISK model was evaluated with a retrospective cohort of 425 patients from the University Hospital Brno, Czech Republic. Two hundred ninety-nine patients were involved in our disease-specific survival analysis; 226 cases with known lymph node status were available for lymph node metastasis analysis. Patients were included undergoing either pelvic lymph node dissection (N = 84) or sentinel node biopsy (N =70) to explore the accuracy of both staging procedures. Results: The area under the curve was 0.84 (95% confidence interval [CI], 0.77-0.9) for lymph node metastasis analysis and 0.86 (95% CI, 0.79-0.93) for 5-year disease-specific survival evaluation, indicating quite positive concordance between prediction and reality. Calibration plots to visualize results demonstrated an outstanding predictive value for low-risk cancers (grades 1-2), whereas outcomes were underestimated among high-risk patients (grade 3), especially in disease-specific survival. This phenomenon was even more obvious when patients were subclassified according to FIGO clinical stages. Conclusions: Our data confirmed ENDORISK model's laudable predictive ability, particularly among patients with a low risk of lymph node metastasis and expected favorable survival. For high-risk and/or advanced stages, the ENDORISK network needs to be additionally trained/improved.

L1CAM expression as a predictor of platinum response in high-risk endometrial carcinoma.

For high-risk endometrial cancer (EC) patients, adjuvant chemotherapy is recommended to improve outcome. Yet, predictive biomarkers for response to platinum-based chemotherapy (Pt-aCT) are currently lacking. We tested expression of L1 cell-adhesion molecule (L1CAM), a well-recognised marker of poor prognosis in EC, in tumour samples from high-risk EC patients, to explore its role as a predictive marker of Pt-aCT response. L1CAM expression was determined using RT-qPCR and immunohistochemistry in a cohort of high-risk EC patients treated with Pt-aCT and validated in a multicentric independent cohort. The association between L1CAM and clinicopathologic features and L1CAM additive value in predicting platinum response were determined. The effect of L1CAM gene silencing on response to carboplatin was functionally tested on primary L1CAM-expressing cells. Increased L1CAM expression at both genetic and protein level correlated with high-grade, non-endometrioid histology and poor response to platinum treatment. A predictive model adding L1CAM to prognostic clinical variables significantly improved platinum response prediction (C-index 78.1%, P = .012). In multivariate survival analysis, L1CAM expression was significantly associated with poor outcome (HR: 2.03, P = .019), potentially through an indirect effect, mediated by its influence on response to chemotherapy. In vitro, inhibition of L1CAM significantly increased cell sensitivity to carboplatin, supporting a mechanistic link between L1CAM expression and response to platinum in EC cells. In conclusion, we have demonstrated the role of L1CAM in the prediction of response to Pt-aCT in two independent cohorts of high-risk EC patients. L1CAM is a promising candidate biomarker to optimise decision making in high-risk patients who are eligible for Pt-aCT.

Improving preoperative diagnosis in endometrial cancer using systematic morphological assessment and a small immunohistochemical panel.

Preoperative histopathological classification determines the primary surgical approach in endometrial carcinoma (EC) patients but has only moderate agreement between preoperative and postoperative diagnosis. The aim of the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study is to determine whether histopathological assessment and a small panel of diagnostic biomarkers decreases discrepancies between preoperative and postoperative diagnosis in EC. Preoperative endometrial tissue of 378 included patients with EC was stained with 15 different antibodies. Clinically relevant discrepancies in grade or histological subtype between original preoperative and reviewed postoperative diagnosis were observed in 75 (20%) patients. Highest clinically relevant discrepancy was found in grade 2 ECs (20%), compared to 5% and 14% in respectively grade 1 and 3 endometrioid endometrial carcinomas (EECs). A practical two-biomarker panel with PR and p53 improved diagnostic accuracy (AUC = 0.92; 95%CI = 0.88-0.95) compared to solely morphological evaluation (AUC = 0.86). In preoperative high-grade EC, the diagnostic accuracy of histological subtype was improved by a three-immunohistochemical biomarker panel (PR, IMP3, and L1CAM) (AUC = 0.93; 95%CI = 0.88-0.98) compared to solely morphological evaluation (AUC = 0.81). In conclusion to improve correct preoperative diagnosis in EC, we recommend use of a panel of at least two easily accessible immunohistochemical biomarkers (PR and p53), only in grade 2 ECs. Overall, this will reduce clinically relevant discrepancies in tumor grade and subtype with postoperative diagnosis with 6% (from 20% to 14%). Addition of PR, IMP3, and L1CAM for histological subtyping in high-grade EECs resulted in a further decrease in discrepancies with 8% (from 20% to 12%).

The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a European Network for Individualized Treatment of Endometrial Cancer collaboration study.

There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group.

Optimizing the treatment algorithm for sentinel lymph node mapping in endometrial cancer.

The incidence of endometrial cancer, the most common gynecological malignancy, is increasing as life expectancy and obesity both rise. Lymph node status is the most important predictor for outcome, yet routine lymphadenectomy does not confer a survival benefit and is associated with substantial surgical morbidity. In the last decade, sentinel lymph node (SLN) mapping has emerged as a feasible and accurate alternative to full lymphadenectomy. Yet, SLN has introduced a distinction between micro- and macrometastasis, and the entity of non-SLN involvement with their attendant impact on outcome. Included among the raised issues is the question of whether positive sentinel nodes should be followed by pelvic and/or para-aortic lymphadenectomy dependent on the presence of macrometastasis at frozen section or other criteria. Moreover, the proper adjuvant treatment for individual cases with micrometastasis and/or isolated tumor cells is unclear. Recently published data on this topic are summarized in order to optimize the current treatment algorithm as it relates to the results of SLN assessment in endometrial cancer.

Impact of different adjuvant treatment approaches on survival in stage III endometrial cancer: A population-based study.

BACKGROUND: Patients with International Federation of Gynaecology and Obstetrics (FIGO) stage III endometrial cancer (EC) have a substantial risk of adverse outcomes. After surgery, adjuvant therapy is recommended with external beam radiotherapy (EBRT), chemotherapy (CT) or both EBRT and CT. Recent trials suggest that EBRT + CT is superior to EBRT or CT alone but also results in more toxicity. We have compared the outcome of different adjuvant treatments in a population-based cohort to identify subgroups that benefit most from EBRT + CT. METHODS: All patients diagnosed with FIGO stage III EC and treated with surgery in 2005-2016 were identified from the Netherlands Cancer Registry. The primary outcome was overall survival (OS); associations with adjuvant treatment were analysed using Cox regression analysis. RESULTS: Among 1241 eligible patients, EBRT + CT was associated with a better OS than CT (hazard ratio [HR] = 1.84, 95% confidence interval [CI] = 1.34-2.52) and EBRT alone (HR = 1.37, 95% CI = 1.05-1.79). In stage IIIC, there was a significant benefit of EBRT + CT compared with CT or EBRT alone. In stage IIIA-B, there was no difference between EBRT + CT or EBRT alone. In endometrioid EC (EEC) and carcinosarcomas, EBRT + CT was associated with a better OS than CT or EBRT alone. For uterine serous cancers, there was no survival benefit of EBRT + CT over CT. In all analysis by stage and histology, any adjuvant treatment was superior to no adjuvant therapy. CONCLUSIONS: In this population-based study, adjuvant EBRT + CT was associated with improved OS compared with CT or EBRT alone in FIGO stage IIIC EC, EEC and carcinosarcoma. This suggests that application of EBRT + CT in stage III should be further stratified according to these subgroups.

Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study.

BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with <5% risk of LNM, with a false-negative rate of 1.6%. A limitation of the study is the use of imputation to correct for missing predictor variables in the development cohort and the retrospective study design. CONCLUSIONS: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.

Fallopian tube abnormalities in uterine serous carcinoma.

OBJECTIVE: Uterine serous carcinoma (USC) is presumed to arise from endometrial intra-epithelial carcinoma (EIC), whereas tubo-ovarian high-grade serous carcinomas have similar precursor lesions in the Fallopian tube, i.e. serous tubal intra-epithelial carcinoma (STIC). The presence of Fallopian tube abnormalities and their clonal relationship to the concurrent USC was investigated. METHODS: In this multicenter study, all patients treated for USC between 1992 and 2017 were retrospectively identified. Histopathological diagnosis of USC, EIC and STIC was revised by an expert pathologist. Additionally, all Fallopian tube sections were immunohistochemically stained (p53 and Ki-67). Fallopian tube abnormalities were classified as either p53 signature, serous tubal intra-epithelial lesion (STIL) or STIC. The USCs and Fallopian tube abnormalities were analyzed by targeted next-generation sequencing. RESULTS: In 168 included patients, Fallopian tube abnormalities were found in 27.4% (46/168): p53-signatures in 17.9% (30/168), STILs in 3.0% (5/168) and STICs in 6.5% (11/168). In subgroup analysis, STICs were found in 9.5% (11/115) of patients with at least one section of the fimbriated end embedded. Next-generation sequencing showed identical TP53-mutations in the STIC and corresponding USC. CONCLUSIONS: In conclusion, the presence of Fallopian tube abnormalities was shown in a high percentage of patients with USC, representing either true precursor lesions or metastasized disease.

Molecular profiling identifies synchronous endometrial and ovarian cancers as metastatic endometrial cancer with favorable clinical outcome.

Synchronous primary endometrial and ovarian cancers (SEOs) represent 10% of all endometrial and ovarian cancers and are assumed to develop as independent entities. We investigated the clonal relationship between endometrial and ovarian carcinomas in a large cohort classified as SEOs or metastatic disease (MD). The molecular profiles were compared to The Cancer Genome Atlas (TCGA) data to explore primary origin. Subsequently, the molecular profiles were correlated with clinical outcome. To this extent, a retrospective multicenter study was performed comparing patients with SEOs (n = 50), endometrial cancer with synchronous ovarian metastasis (n = 19) and ovarian cancer with synchronous endometrial metastasis (n = 20). Targeted next-generation sequencing was used, and a clonality index was calculated. Subsequently, cases were classified as POLE mutated, mismatch repair deficient (MMR-D), TP53-wild-type or TP53-mutated. In 92% of SEOs (46/50), the endometrial and concurrent ovarian carcinoma shared at least one somatic mutation, with a clonality index above 0.95, supporting a clonal origin. The SEO molecular profiles showed striking similarities with the TCGA endometrial carcinoma set. SEOs behaved distinctly different from metastatic disease, with a superior outcome compared to endometrial MD cases (p < 0.001) and ovarian MD cases (p < 0.001). Classification according to the TCGA identified four groups with different clinical outcomes. TP53 mutations and extra-utero-ovarian disease were independent predictors for poor clinical outcome. Concluding, SEOs were clonally related in an overwhelming majority of cases and showed a favorable prognosis. Their molecular profile implied a primary endometrial origin. TP53 mutation and extra-utero-ovarian disease were independent predictors for outcome, and may impact adjuvant systemic treatment planning.

Mutational analysis of cervical cytology improves diagnosis of endometrial cancer: A prospective multicentre cohort study.

Endometrial carcinoma (EC) is traditionally diagnosed by a histopathological assessment of an endometrial biopsy, leaving up to 30% of patients undiagnosed due to technical failure or an inadequate amount of tissue. The aim of the current study is to assess whether mutational analysis of cervical cytology or pipelle endometrial biopsies improves the diagnostic accuracy of traditional histopathological diagnosis of EC. This prospective multicentre cohort study included patients surgically treated for EC or a benign gynaecological condition (control group). A Pap brush sample, cervicovaginal self-sample, pipelle endometrial biopsy and surgical specimen of either the EC or normal endometrium were obtained. A targeted next-generation sequencing panel was used to analyse these samples for mutations in eight genes. Sensitivity, specificity and predictive values were calculated. Fifty-nine EC patients and 31 control patients were included. In these patients, traditional histopathological diagnosis by pipelle had a sensitivity of 79% and a specificity of 100%. For EC patients, 97% of surgical specimens contained at least one mutation. Mutational analysis of Pap brush samples, self-samples and pipelle endometrial biopsies yielded a sensitivity of 78, 67 and 96% with a specificity of 97, 97 and 94%, respectively. Combining one of these three methods with histopathological pipelle endometrial biopsy evaluations yielded a sensitivity of 96, 93 and 96%, respectively. Our study has shown that mutational analysis of either cervical cytology or pipelle endometrial biopsies improves diagnosis of EC. Prospective validation will support implementation in clinical practice.