A Novel Approach to Preoperative Risk Stratification in Endometrial Cancer: The Added Value of Immunohistochemical Markers

Pulmonary metastasis of stage I, low-grade endometrioid carcinoma: two case reports and the literature review

Endometrial cancer (EC) is the most common malignant tumor of the female reproductive system, and the majority of ECs are low histological grade and confined to the uterus, resulting in a good prognosis. However, metastasis to the lung from a low-grade and early-stage endometrial endometrioid carcinoma (EEC) is extremely rare. Therefore, it is crucial to accurately differentiate between primary pulmonary malignancy and extra-thoracic malignancy presenting as metastatic disease, and flexible bronchoscopy with tissue acquisition plays a key role in this process. Despite its importance, there is limited literature available on the cytology of metastatic endometrial carcinoma in liquid-based cytology of bronchial brush (BB). In this article, we present two rare cases of lung metastasis from low-grade and early-stage EEC, along with a detailed analysis of the cytologic features observed in BB samples. These cases highlight the significance of cytological and histological pathology, complemented by immunohistochemistry (ICH) analysis, in the diagnosis and management of EEC patients. Pathologists should pay close attention to these aspects, while gynecologists need to be mindful of the follow-up and management of early-stage, low-grade EEC patients. By focusing on these areas, healthcare professionals can effectively contribute to the improved care and outcomes of patients with EEC.

Estrogen/Progesterone Receptor Loss, CTNNB1 and KRAS Mutations Are Associated With Local Recurrence or Distant Metastasis in Low-Grade Endometrial Endometrioid Carcinoma

A subset of endometrial endometrioid carcinomas (EECs) with low-grade histology recur with poor outcomes. Published evidence suggests that poor outcomes may be associated with loss of expression of ER-alpha (ER-α) as well as with β-Catenin-1 ( CTNNB1 ) and Kirsten rat sarcoma viral oncogene homolog ( KRAS ) mutations. This study reports on institutional experience with the incidence of recurrence in low-grade EEC and their association with CTNNB1 and KRAS mutations as well as estrogen/progesterone receptor (ER/PR) expression. Forty-eight (8.5%) out of 568 cases of low-grade EEC with biopsy-proven recurrence were identified; and were analyzed by immunohistochemistry for ER, PR, p53, MMR protein, and mutation analysis for exon 3 of the CTNNB1 and exon 2 of KRAS in relation to recurrence type, local or distant metastasis/recurrence. Twenty-three patients (4%) developed local, and 25 patients (4.4%) developed distant metastases/recurrence. Decreased expression or loss of ER/PR was found in 17/44 (38.6%) patients with recurrence. Eighty-four percent of patients with low-grade EEC and local recurrence had CTNNB1 mutations. Seventy-three percent of patients with distant metastasis/recurrence had KRAS mutations. The association of these mutations with the type of recurrence was statistically significant for both. Five cases with the morphology of low-grade EEC were reclassified as mesonephric-like carcinoma and were universally characterized by distant metastasis/recurrence, loss of ER/PR expression, large tumor size, absence of CTNNB1 mutations, and the presence of KRAS mutations. In low-grade EEC, CTNNB1 and KRAS mutations are associated with local recurrence and distant metastasis/recurrence, respectively, suggesting that these 2 different progression types may be conditioned by tumor genotype. ER/PR immunohistochemistry may be helpful in identifying poor performers in low-grade EEC. Furthermore, identification of the decreased expression or loss of ER/PR in tumors with low-grade histology should prompt consideration of mesonephric-like carcinoma, which is a more aggressive tumor than the low-grade EEC. KRAS mutations were associated with distant metastasis/recurrence in tumors with and without mesonephric-like phenotype.

The Co-Expression of Estrogen Receptors ERα, ERβ, and GPER in Endometrial Cancer

Estrogens have important roles in endometrial cancer (EC) and exert biological effects through the classical estrogen receptors (ERs) ERα and ERβ, and the G-protein-coupled ER, GPER. So far, the co-expression of these three types of ERs has not been studied in EC. We investigated ERα, ERβ, GPER mRNA and protein levels, and their intracellular protein distributions in EC tissue and in adjacent control endometrial tissue. Compared to control endometrial tissue, immunoreactivity for ERα in EC tissue was weaker for nuclei with minor, but unchanged, cytoplasmic staining; mRNA and protein levels showed decreased patterns for ERα in EC tissue. For ERβ, across both tissue types, the immunoreactivity was unchanged for nuclei and cytoplasm, although EC tissues again showed lower mRNA and protein levels compared to adjacent control endometrial tissue. The immunoreactivity of GPER as well as mRNA levels of GPER were unchanged across cancer and control endometrial tissues, while protein levels were lower in EC tissue. Statistically significant correlations of estrogen receptor α (ESR1) versus estrogen receptor β (ESR2) and GPER variant 3,4 versus ESR1 and ESR2 was seen at the mRNA level. At the protein level studied with Western blotting, there was significant correlation of ERα versus GPER, and ERβ versus GPER. While in clinical practice the expression of ERα is routinely tested in EC tissue, ERβ and GPER need to be further studied to examine their potential as prognostic markers, provided that specific and validated antibodies are available.

p53, Pirh2, and L1CAM as Promising Prognostic Biomarkers of Endometrial Carcinoma: An Immunohistochemical and Genetic Study

Endometrial cancer (EC) is the most common gynecologic cancer and the current methods for the prediction of its prognosis and treatment response are unfortunately suboptimal. In this study, we evaluated the prognostic value of p53, Pirh2, and L1CAM in 60 cases of EC using immunohistochemistry (IHC) and polymerase chain reaction. TP53 missense mutations result in nuclear accumulation of p53 protein that can be detected as overexpression by IHC. This is in the form of diffuse strong nuclear positivity involving at least at least >50% of the tumor cells as a whole or if >50% of the tumor cells of a discrete geographical areas. Abnormal p53 IHC expression was expressed in 33.3% of the cases and significantly associated with the tumor grade, myometrial invasion (MI), lymphovascular invasion (LVSI), nodal metastasis, and FIGO stage, and the advanced European Society for Medical Oncology (ESMO) risk groups (P<0.001 for each). High IHC Pirh2 expression was noted in 58.3% of the cases, and significantly associated with MI, LVSI, nodal metastasis, FIGO stage, and high-risk group (P<0.001, P=0.011, P=0.010, P=0.024, P=0.005, respectively). There was a significant upregulation of Pirh2 mRNA expression in EC specimens as compared with the control adjacent tissues (P=0.001). Upregulated Pirh2 mRNA expression had a significant association with Pirh2 immunostaining, tumor grade, tumor stage, MI, lymph node involvement, LVSI, and relapse (P<0.001 for each). Positive L1CAM immunoexpression was noted in 26.7% and was significantly associated with grade, MI, LVSI, nodal metastasis, FIGO stage, and high-risk group (P=0.003, P=0.023, P=0.003, P<0.001, P<0.001, P=0.002, respectively). Analysis of follow-up period revealed that EC with abnormal p53 IHC expression, high pirh2 and positive L1CAM expression exhibited a potent relation with tumor relapse, shorter overall survival and disease-specific survival (P<0.001 for each). Mutant p53, high Pirh2, and L1CAM-positive EC are highly aggressive tumors with a shortened survival rate, dismal outcome, and high risk of relapse after the standard protocol of therapy.

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.

Current and Emerging Prognostic Biomarkers in Endometrial Cancer

Endometrial cancer is the most common gynaecological malignancy in high income countries and its incidence is rising. Whilst most women with endometrial cancer are diagnosed with highly curable disease and have good outcomes, a significant minority present with adverse clinico-pathological characteristics that herald a poor prognosis. Prognostic biomarkers that reliably select those at greatest risk of disease recurrence and death can guide management strategies to ensure that patients receive appropriate evidence-based and personalised care. The Cancer Genome Atlas substantially advanced our understanding of the molecular diversity of endometrial cancer and informed the development of simplified, pragmatic and cost-effective classifiers with prognostic implications and potential for clinical translation. Several blood-based biomarkers including proteins, metabolites, circulating tumour cells, circulating tumour DNA and inflammatory parameters have also shown promise for endometrial cancer risk assessment. This review provides an update on the established and emerging prognostic biomarkers in endometrial cancer.

L1CAM is not a reliable predictor for lymph node metastases in endometrial cancer, but L1CAM positive patients benefit from radiotherapy

Purpose: Several studies evidenced the potential of L1CAM as a prognostic marker in endometrial cancer. The aim of this study was to investigate whether L1CAM can predict lymph node metastasis and could therefore be used preoperatively to identify patients with low to high-intermediate risk endometrial cancer who would profit from a lymphadenectomy and an adjuvant treatment. To avoid unnecessary morbidity, de-escalating strategies are still required.

Methods: Immunohistochemistry for L1CAM was performed on curettage or hysterectomy specimens from 212 patients diagnosed with endometrial cancer who were treated at the University Hospital Basel during 2011-2019. L1CAM expression was correlated with clinicopathological features such as histological subtype, FIGO stage, lymph node metastasis, lymphadenectomy, adjuvant treatment and outcome.

Results: Using a cut off ≥10%, L1CAM was positive in 41/212 patients (19.3%) and negative in 171/212 patients (80.7%). L1CAM was associated with high-risk features such as non-endometrioid histology, high tumour grade, and high FIGO stage. There was no significant correlation between L1CAM expression and lymph node metastasis. However, patients with L1CAM positive tumours showed improved disease-specific survival if treated with adjuvant radiotherapy.

Conclusion: Although L1CAM expression pointed towards aggressive tumour biology, preoperative L1CAM analysis did not add any substantial predictive information regarding lymph node metastasis in low to high-intermediate risk groups. Therefore, L1CAM status is not suitable to tailor the surgical algorithm for lymph node staging. Nevertheless, our results suggest that L1CAM could be used as a predictive biomarker to select patients who may benefit the most from adjuvant radiotherapy.

Pre-treatment risk assessment of women with endometrial cancer: differences in outcomes of molecular and clinical classifications in the Slovenian patient cohort

Background

The aim of this study was to evaluate changes in prognostic risk profiles of women with endometrial cancer by comparing the clinical risk assessment with the integrated molecular risk assessment profiling.

Patients and methods

This prospective study recruited patients with biopsy proven endometrial cancer treated at the University Medical Centre Maribor between January 2020 to February 2021. Patient clinical data was assessed and categorized according to the currently valid European Society of Gynaecological Oncology, European SocieTy for Radiotherapy and Oncology, and European Society of Pathology (ESGO/ESTRO/ESP) guidelines on endometrial cancer. Molecular tumour characterization included determination of exonuclease domain of DNA polymerase-epsilon (POLE) mutational status by Sanger sequencing and imunohistochemical specimen evaluation on the presence of mismatch repair deficiencies (MMRd) and p53 abnormalities (p53abn).

Results

Fourty-five women were included in the study. Twenty-two tumours were of non-specific mutational profile (NSMP) (56.4%), 13 were classified as MMRd (33.3%), 3 were classified as p53abn (7.7%) and 1 was classified as POLE mutated (2.6%). Six tumours (15.4%) had multiple molecular classifiers, these were studied separately and were not included in the risk assessment. The clinical risk-assessment classified 21 women (53.8%) as low-risk, 5 women (12.8%) as intermediate risk, 2 women as high-intermediate risk (5.1%), 10 women (25.6%) as high risk and 1 patient as advanced metastatic (2.6%). The integrated molecular classification changed risk for 4 women (10.3%).

Conclusions

Integrated molecular risk improves personalized risk assessment in endometrial cancer and could potentially improve therapeutic precision. Further molecular stratification with biomarkers is especially needed in the NSMP group to improve personalized risk-assessment.

Preoperative MRI and immunohistochemical examination for the prediction of high-risk endometrial cancer

Background

Magnetic resonance imaging (MRI) and immunohistochemical (IHC) examination provides useful information for the risk stratification of endometrial cancer (EC). However, the use of the combination of MRI and IHC for the prediction of high-risk EC is controversial. The aim of this study was to evaluate the value of preoperative MRI and IHC examination in prediction of patients with high-risk EC.

Methods

This retrospective case-control study was conducted from January 1, 2018 to May 1, 2021 at two hospitals. A primary cohort (n=102) comprised patients with histologically confirmed EC in one hospital between January 1, 2018 and May 31, 2020. An additional external cohort (n=35) comprising patients with histologically confirmed EC in a different hospital from January 1, 2020 to May 1, 2021 was included for validation. Imaging features including tumor size, tumor margin, relative T2 value, tumor signal intensity on diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) were determined from preoperative MRI images. IHC markers including ER, PR, p53 and Ki67 were determined through IHC staining of preoperative curettage specimen. Patients were divided into high-risk and low-intermediate- risk group based on the final histological results. Differences between categorical and numerical variables were assessed using chi-square test and independent-sample t-test, respectively. Multivariate binary logistic regression analyses were used for construction of the prediction model A fusion prediction model was constructed by combining MRI features and IHC markers. The predictive performance of the model was then validated using the external cohort.

Results

Imaging and IHC markers were significantly associated with risk ranks. Model 1 based on MRI features showed an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.741-0.903] whereas Model 2 based on IHC markers showed an AUC of 0.894 (95% CI, 0.829-0.960). Notably, model 3 integrating independent MRI and IHC risk factors demonstrated good calibration and high differentiation ability with an AUC of 0.958 (95% CI, 0.923-0.993), and showed good discrimination with an AUC of 0.84 (95% CI, 0.677-0.942) using the external validation set.

Conclusions

This study proposes a comprehensive predictive model comprising MRI and IHC features as a powerful tool for preoperative risk stratification to assist in clinical decision-making for EC patients.

Endometrial Cancer Molecular Characterization: The Key to Identifying High-Risk Patients and Defining Guidelines for Clinical Decision-Making?

Endometrial carcinomas (EC) are the sixth most common cancer in women worldwide and the most prevalent in the developed world. ECs have been historically sub-classified in two major groups, type I and type II, based primarily on histopathological characteristics. Notwithstanding the usefulness of such classification in the clinics, until now it failed to adequately stratify patients preoperatively into low- or high-risk groups. Pieces of evidence point to the fact that molecular features could also serve as a base for better patients' risk stratification and treatment decision-making. The Cancer Genome Atlas (TCGA), back in 2013, redefined EC into four main molecular subgroups. Despite the high hopes that welcomed the possibility to incorporate molecular features into practice, currently they have not been systematically applied in the clinics. Here, we outline how the emerging molecular patterns can be used as prognostic factors together with tumor histopathology and grade, and how they can help to identify high-risk EC subpopulations for better risk stratification and treatment strategy improvement. Considering the importance of the use of preclinical models in translational research, we also discuss how the new patient-derived models can help in identifying novel potential targets and help in treatment decisions.

Tumor Characteristic Variations between Symptomatic and Asymptomatic Endometrial Cancer

Endometrial cancer is the most common gynecologic malignancy in Europe and usually diagnosed in its initial stage owing to early symptoms of abnormal bleeding. There is no population screening for this disease, although it can sometimes be accidentally diagnosed in asymptomatic patients. Our study aims to determine differences in clinical and tumor characteristics between an asymptomatic and symptomatic group of patients. This unicentric prospective observational study took place in University Hospital Brno between January 2016 and December 2019. A total of 264 patients met inclusion criteria (26% asymptomatic, 74% with reported symptoms). We did not find a statistically significant difference in clinical characteristics (menopausal status, parity, age, BMI, and serum level of CA 125) between groups. According to ultrasound examination, bleeding tumors were larger (19.5 vs. 12.7 mm, p ≤ 0.001). Definitive histology results indicated more frequent lymphovascular space invasion (p < 0.001), along with deep myometrial (p = 0.001) and cervical (p = 0.002) invasion. There was no difference in advanced stages of the tumor. We did not substantiate statistically significant difference in immunohistochemical profile (estrogen and progesterone receptors, L1 cell adhesion molecule, tumor protein p53), which is relevant for tumor recurrence risk and survival capacity. Our conclusions affirmed that bleeding occurs more often among patients with local tumor invasion into the myometrium and cervical stroma. Final International Federation of Gynecology and Obstetrics (FIGO) stage, histology, and immunohistochemical characteristics do not significantly affect symptom appearance.

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.

The significance of plasma D-dimer level in predicting high risk factors of endometrial cancer

Background

Activated clotting-fibrinolytic system is associated with poor outcome of cancer patients. This retrospective study aimed to evaluate the significance of plasma D-dimer level in predicting high risk factors of endometrial cancer (EC) patients.

Methods

Total 176 EC patients who underwent radiotherapy between January 2018 and June 2019 at Shanghai First Maternity and Infant Hospital were retrospectively analyzed. Their preoperative and postoperative plasma D-dimer levels were measured as routine assessment in our hospital, and analyzed for their association with clinicopathological data retrieved from medical records of the patients.

Results

High risk group had significantly higher 1st day postoperative D-dimer levels. The 1st day postoperative D-dimer predicted higher grade EC with the specificity of 63.7% and the sensitivity of 63.4%; predicted late stage EC with the specificity of 83.7% and the sensitivity of 58.6%; predicted deeper myoinvasion of EC with the specificity of 84.9% and the sensitivity of 43.3%; predicted lymphovascular space invasion positive EC with the specificity of 84.0% and the sensitivity of 50.0%; predicted lymph node metastasis of EC with the specificity of 50.9% and the sensitivity of 100%; and predicted cervical invasion of EC with the specificity of 82.1% and the sensitivity of 65.0%.

Conclusions

Increased postoperative plasma D-dimer levels accurately predicted high risk factors in patients with EC.

Genomics Score Based on Genome-Wide Network Analysis for Prediction of Survival in Gastric Cancer: A Novel Prognostic Signature

Purpose

Gastric cancer (GC) is a product of multiple genetic abnormalities, including genetic and epigenetic modifications. This study aimed to integrate various biomolecules, such as miRNAs, mRNA, and DNA methylation, into a genome-wide network and develop a nomogram for predicting the overall survival (OS) of GC.

Materials and Methods

A total of 329 GC cases, as a training cohort with a random of 150 examples included as a validation cohort, were screened from The Cancer Genome Atlas database. A genome-wide network was constructed based on a combination of univariate Cox regression and least absolute shrinkage and selection operator analyses, and a nomogram was established to predict 1-, 3-, and 5-year OS in the training cohort. The nomogram was then assessed in terms of calibration, discrimination, and clinical usefulness in the validation cohort. Afterward, in order to confirm the superiority of the whole gene network model and further reduce the biomarkers for the improvement of clinical usefulness, we also constructed eight other models according to the different combinations of miRNAs, mRNA, and DNA methylation sites and made corresponding comparisons. Finally, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also performed to describe the function of this genome-wide network.

Results

A multivariate analysis revealed a novel prognostic factor, a genomics score (GS) comprising seven miRNAs, eight mRNA, and 19 DNA methylation sites. In the validation cohort, comparing to patients with low GS, high-GS patients (HR, 12.886; P < 0.001) were significantly associated with increased all-cause mortality. Furthermore, after stratification of the TNM stage (I, II, III, and IV), there were significant differences revealed in the survival rates between the high-GS and low-GS groups as well (P < 0.001). The 1-, 3-, and 5-year C-index of whole genomics-based nomogram were 0.868, 0.895, and 0.928, respectively. The other models have comparable or relatively poor comprehensive performance, while they had fewer biomarkers. Besides that, DAVID 6.8 further revealed multiple molecules and pathways related to the genome-wide network, such as cytomembranes, cell cycle, and adipocytokine signaling.

Conclusion

We successfully developed a GS based on genome-wide network, which may represent a novel prognostic factor for GC. A combination of GS and TNM staging provides additional precision in stratifying patients with different OS prognoses, constituting a more comprehensive sub-typing system. This could potentially play an important role in future clinical practice.

Fertility-sparing treatment in early endometrial cancer: current state and future strategies

Endometrial cancer (EC) is the fifth most common cancer in women worldwide. Global estimates show rising incidence rates in both developed and developing countries. Most women are diagnosed postmenopausal, but 14–25% of patients are premenopausal and 5% are under 40 years of age. Established risk factors include age and hyperestrogenic status associated with nulliparity, obesity, and metabolic syndrome. Standard treatment for EC, which involves total hysterectomy and bilateral salpingo-oophorectomy, has excellent survival outcomes, particularly for low-grade endometrioid tumors. However, it leads to permanent loss of fertility among women who wish to preserve their reproductive potential. With current trends of reproductive-age women delaying childbearing, rising EC incidence rates, and a growing epidemic of obesity, particularly in developed countries, research on conservative non-surgical treatment approaches remains a top priority. Fertility-sparing treatment predominantly involves the use of oral progestins and levonorgestrel-releasing intrauterine devices, which have been shown to be feasible and safe in women with early stage EC and minimal or no myometrial invasion. However, data on the efficacy and safety of conservative management strategies are primarily based on retrospective studies. Randomized clinical trials in younger women and high-risk obese patients are currently underway. Here, we have presented a comprehensive review of the current literature on conservative, fertility-sparing approaches, defining the optimal candidates and evaluating tumor characteristics, reproductive and oncologic outcomes, and ongoing clinical trials. We have also summarized current guidelines and recommendations based on the published literature.

Improving response to progestin treatment of low-grade endometrial cancer

OBJECTIVES

This review examines how response rates to progestin treatment of low-grade endometrial cancer can be improved. In addition to providing a brief overview of the pathogenesis of low-grade endometrial cancer, we discuss limitations in the current classification of endometrial cancer and how stratification may be refined using molecular markers to reproducibly identify 'low-risk' cancers which may represent the best candidates for progestin therapy. We also discuss constraints in current approaches to progestin treatment of low-grade endometrial cancer and perform a systematic review of predictive biomarkers.

METHODS

PubMed, ClinicalTrials.gov, and Cochrane Library were searched for studies reporting pre-treatment biomarkers associated with outcome in women with low-grade endometrial cancer or endometrial hyperplasia with an intact uterus who received progestin treatment. Studies of fewer than 50 women were excluded. The study protocol was registered in PROSPERO (ID 152374). A descriptive synthesis of pre-treatment predictive biomarkers reported in the included studies was conducted.

RESULTS

Of 1908 records reviewed, 19 studies were included. Clinical features such as age or body mass index cannot predict progestin response. Lesions defined as 'low-risk' by FIGO criteria (stage 1A, grade 1) can respond well; however, the reproducibility and prognostic ability of the current histopathological classification system is suboptimal. Molecular markers can be reproducibly assessed, have been validated as prognostic biomarkers, and may inform patient selection for progestin treatment. DNA polymerase epsilon (POLE)-ultramutated tumors and a subset of p53 wild-type or DNA mismatch repair (MMR)-deficient tumors with 'low-risk' features (eg, progesterone and estrogen receptor-positive) may have improved response rates, though this needs to be validated.

DISCUSSION

Molecular markers can identify cases which may be candidates for progestin treatment. More work is needed to validate these biomarkers and potentially identify new ones. Predictive biomarkers are anticipated to inform future research into progestin treatment of low-grade endometrial cancer and ultimately improve patient outcomes.